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A search for the supersymmetric partners of quarks and gluons (squarks and gluinos) in final states containing hadronic jets and missing transverse momentum, but no electrons or muons, is presented. The data used in this search were recorded in 2015 and 2016 by the ATLAS experiment in $\sqrt{s}$=13 TeV proton--proton collisions at the Large Hadron Collider, corresponding to an integrated luminosity of 36.1 fb$^{-1}$. The results are interpreted in the context of various models where squarks and gluinos are pair-produced and the neutralino is the lightest supersymmetric particle. An exclusion limit at the 95\% confidence level on the mass of the gluino is set at 2.03 TeV for a simplified model incorporating only a gluino and the lightest neutralino, assuming the lightest neutralino is massless. For a simplified model involving the strong production of mass-degenerate first- and second-generation squarks, squark masses below 1.55 TeV are excluded if the lightest neutralino is massless. These limits substantially extend the region of supersymmetric parameter space previously excluded by searches with the ATLAS detector.
The results of a search for electroweakino pair production $pp \rightarrow \tilde\chi^\pm_1 \tilde\chi^0_2$ in which the chargino ($\tilde\chi^\pm_1$) decays into a $W$ boson and the lightest neutralino ($\tilde\chi^0_1$), while the heavier neutralino ($\tilde\chi^0_2$) decays into the Standard Model 125 GeV Higgs boson and a second $\tilde\chi^0_1$ are presented. The signal selection requires a pair of $b$-tagged jets consistent with those from a Higgs boson decay, and either an electron or a muon from the $W$ boson decay, together with missing transverse momentum from the corresponding neutrino and the stable neutralinos. The analysis is based on data corresponding to 139 $\mathrm{fb}^{-1}$ of $\sqrt{s}=13$ TeV $pp$ collisions provided by the Large Hadron Collider and recorded by the ATLAS detector. No statistically significant evidence of an excess of events above the Standard Model expectation is found. Limits are set on the direct production of the electroweakinos in simplified models, assuming pure wino cross-sections. Masses of $\tilde{\chi}^{\pm}_{1}/\tilde{\chi}^{0}_{2}$ up to 740 GeV are excluded at 95% confidence level for a massless $\tilde{\chi}^{0}_{1}$.
The post-fit $m_{CT}$ distribution is shown in the validation region VR-onLM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.
The post-fit $m_{CT}$ distribution is shown in the validation region VR-onLM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.
The post-fit $m_{CT}$ distribution is shown in the validation region VR-onLM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.
The post-fit $m_{CT}$ distribution is shown in the validation region VR-onLM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.
The post-fit $m_{CT}$ distribution is shown in the validation region VR-onMM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.
The post-fit $m_{CT}$ distribution is shown in the validation region VR-onMM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.
The post-fit $m_{CT}$ distribution is shown in the validation region VR-onMM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.
The post-fit $m_{CT}$ distribution is shown in the validation region VR-onMM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.
The post-fit $m_{CT}$ distribution is shown in the validation region VR-onHM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.
The post-fit $m_{CT}$ distribution is shown in the validation region VR-onHM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.
The post-fit $m_{CT}$ distribution is shown in the validation region VR-onHM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.
The post-fit $m_{CT}$ distribution is shown in the validation region VR-onHM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.
The post-fit $m_{CT}$ distribution is shown in the validation region VR-offLM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.
The post-fit $m_{CT}$ distribution is shown in the validation region VR-offLM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.
The post-fit $m_{CT}$ distribution is shown in the validation region VR-offLM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.
The post-fit $m_{CT}$ distribution is shown in the validation region VR-offLM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.
The post-fit $m_{CT}$ distribution is shown in the validation region VR-offMM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.
The post-fit $m_{CT}$ distribution is shown in the validation region VR-offMM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.
The post-fit $m_{CT}$ distribution is shown in the validation region VR-offMM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.
The post-fit $m_{CT}$ distribution is shown in the validation region VR-offMM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.
The post-fit $m_{CT}$ distribution is shown in the validation region VR-offHM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.
The post-fit $m_{CT}$ distribution is shown in the validation region VR-offHM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.
The post-fit $m_{CT}$ distribution is shown in the validation region VR-offHM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.
The post-fit $m_{CT}$ distribution is shown in the validation region VR-offHM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.
The post-fit $m_{CT}$ distribution for SR-HM. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The overflow events, where present, are included in the last bin.
The post-fit $m_{CT}$ distribution for SR-HM. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The overflow events, where present, are included in the last bin.
The post-fit $m_{CT}$ distribution for SR-HM. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The overflow events, where present, are included in the last bin.
The post-fit $m_{CT}$ distribution for SR-HM. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The overflow events, where present, are included in the last bin.
The post-fit $m_{CT}$ distribution for SR-MM. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The overflow events, where present, are included in the last bin.
The post-fit $m_{CT}$ distribution for SR-MM. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The overflow events, where present, are included in the last bin.
The post-fit $m_{CT}$ distribution for SR-MM. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The overflow events, where present, are included in the last bin.
The post-fit $m_{CT}$ distribution for SR-MM. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The overflow events, where present, are included in the last bin.
The post-fit $m_{CT}$ distribution for SR-LM. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The overflow events, where present, are included in the last bin.
The post-fit $m_{CT}$ distribution for SR-LM. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The overflow events, where present, are included in the last bin.
The post-fit $m_{CT}$ distribution for SR-LM. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The overflow events, where present, are included in the last bin.
The post-fit $m_{CT}$ distribution for SR-LM. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The overflow events, where present, are included in the last bin.
The post-fit $m_{bb}$ distribution is shown in the signal region SR-HM after all the selection requirements are applied other than the $m_{bb}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The red line with arrow indicates the $m_{bb}$ cut used in SR selection.The overflow events, where present, are included in the last bin.
The post-fit $m_{bb}$ distribution is shown in the signal region SR-HM after all the selection requirements are applied other than the $m_{bb}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The red line with arrow indicates the $m_{bb}$ cut used in SR selection.The overflow events, where present, are included in the last bin.
The post-fit $m_{bb}$ distribution is shown in the signal region SR-HM after all the selection requirements are applied other than the $m_{bb}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The red line with arrow indicates the $m_{bb}$ cut used in SR selection.The overflow events, where present, are included in the last bin.
The post-fit $m_{bb}$ distribution is shown in the signal region SR-HM after all the selection requirements are applied other than the $m_{bb}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The red line with arrow indicates the $m_{bb}$ cut used in SR selection.The overflow events, where present, are included in the last bin.
The post-fit $m_{bb}$ distribution is shown in the signal region SR-MM after all the selection requirements are applied other than the $m_{bb}$ cut. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The red line with arrow indicates the $m_{bb}$ cut used in SR selection. The overflow events, where present, are included in the last bin.
The post-fit $m_{bb}$ distribution is shown in the signal region SR-MM after all the selection requirements are applied other than the $m_{bb}$ cut. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The red line with arrow indicates the $m_{bb}$ cut used in SR selection. The overflow events, where present, are included in the last bin.
The post-fit $m_{bb}$ distribution is shown in the signal region SR-MM after all the selection requirements are applied other than the $m_{bb}$ cut. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The red line with arrow indicates the $m_{bb}$ cut used in SR selection. The overflow events, where present, are included in the last bin.
The post-fit $m_{bb}$ distribution is shown in the signal region SR-MM after all the selection requirements are applied other than the $m_{bb}$ cut. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The red line with arrow indicates the $m_{bb}$ cut used in SR selection. The overflow events, where present, are included in the last bin.
The post-fit $m_{bb}$ distribution is shown in the signal region SR-LM after all the selection requirements are applied other than the $m_{bb}$ cut. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The red line with arrow indicates the $m_{bb}$ cut used in SR selection. The overflow events, where present, are included in the last bin.
The post-fit $m_{bb}$ distribution is shown in the signal region SR-LM after all the selection requirements are applied other than the $m_{bb}$ cut. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The red line with arrow indicates the $m_{bb}$ cut used in SR selection. The overflow events, where present, are included in the last bin.
The post-fit $m_{bb}$ distribution is shown in the signal region SR-LM after all the selection requirements are applied other than the $m_{bb}$ cut. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The red line with arrow indicates the $m_{bb}$ cut used in SR selection. The overflow events, where present, are included in the last bin.
The post-fit $m_{bb}$ distribution is shown in the signal region SR-LM after all the selection requirements are applied other than the $m_{bb}$ cut. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The red line with arrow indicates the $m_{bb}$ cut used in SR selection. The overflow events, where present, are included in the last bin.
The observed exclusion for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. Experimental and theoretical systematic uncertainties are applied to background and signal samples and illustrated by the yellow band and the red dotted contour lines, respectively. The red dotted lines indicate the $\pm$ 1 standard-deviation variation on the observed exclusion limit due to theoretical uncertainties in the signal cross-section.
The observed exclusion for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. Experimental and theoretical systematic uncertainties are applied to background and signal samples and illustrated by the yellow band and the red dotted contour lines, respectively. The red dotted lines indicate the $\pm$ 1 standard-deviation variation on the observed exclusion limit due to theoretical uncertainties in the signal cross-section.
The observed exclusion for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. Experimental and theoretical systematic uncertainties are applied to background and signal samples and illustrated by the yellow band and the red dotted contour lines, respectively. The red dotted lines indicate the $\pm$ 1 standard-deviation variation on the observed exclusion limit due to theoretical uncertainties in the signal cross-section.
The observed exclusion for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. Experimental and theoretical systematic uncertainties are applied to background and signal samples and illustrated by the yellow band and the red dotted contour lines, respectively. The red dotted lines indicate the $\pm$ 1 standard-deviation variation on the observed exclusion limit due to theoretical uncertainties in the signal cross-section.
The observed exclusion up limit for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. The red dotted lines indicate the $\pm 1 \sigma$ on the observed exclusion limit due to the theoretical uncertainties in the signal cross-section.
The observed exclusion up limit for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. The red dotted lines indicate the $\pm 1 \sigma$ on the observed exclusion limit due to the theoretical uncertainties in the signal cross-section.
The observed exclusion up limit for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. The red dotted lines indicate the $\pm 1 \sigma$ on the observed exclusion limit due to the theoretical uncertainties in the signal cross-section.
The observed exclusion up limit for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. The red dotted lines indicate the $\pm 1 \sigma$ on the observed exclusion limit due to the theoretical uncertainties in the signal cross-section.
The observed exclusion down limit for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. The red dotted lines indicate the $\pm 1 \sigma$ on the observed exclusion limit due to the theoretical uncertainties in the signal cross-section.
The observed exclusion down limit for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. The red dotted lines indicate the $\pm 1 \sigma$ on the observed exclusion limit due to the theoretical uncertainties in the signal cross-section.
The observed exclusion down limit for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. The red dotted lines indicate the $\pm 1 \sigma$ on the observed exclusion limit due to the theoretical uncertainties in the signal cross-section.
The observed exclusion down limit for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. The red dotted lines indicate the $\pm 1 \sigma$ on the observed exclusion limit due to the theoretical uncertainties in the signal cross-section.
The expected exclusion for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. Experimental and theoretical systematic uncertainties are applied to background and signal samples and illustrated by the yellow band and the red dotted contour lines, respectively. The red dotted lines indicate the $\pm$ 1 standard-deviation variation on the observed exclusion limit due to theoretical uncertainties in the signal cross-section.
The expected exclusion for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. Experimental and theoretical systematic uncertainties are applied to background and signal samples and illustrated by the yellow band and the red dotted contour lines, respectively. The red dotted lines indicate the $\pm$ 1 standard-deviation variation on the observed exclusion limit due to theoretical uncertainties in the signal cross-section.
The expected exclusion for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. Experimental and theoretical systematic uncertainties are applied to background and signal samples and illustrated by the yellow band and the red dotted contour lines, respectively. The red dotted lines indicate the $\pm$ 1 standard-deviation variation on the observed exclusion limit due to theoretical uncertainties in the signal cross-section.
The expected exclusion for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. Experimental and theoretical systematic uncertainties are applied to background and signal samples and illustrated by the yellow band and the red dotted contour lines, respectively. The red dotted lines indicate the $\pm$ 1 standard-deviation variation on the observed exclusion limit due to theoretical uncertainties in the signal cross-section.
Upper limits on the cross sections for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Upper limits on the cross sections for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Upper limits on the cross sections for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Upper limits on the cross sections for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-LM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-LM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-LM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-LM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-LM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-LM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-LM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-LM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-LM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-LM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-LM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-LM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-LM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-LM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-LM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-LM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-MM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-MM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-MM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-MM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-MM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-MM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-MM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-MM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-MM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-MM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-MM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-MM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-MM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-MM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-HM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. 1lb\bar{b}$ production
Signal acceptance in SR-HM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. 1lb\bar{b}$ production
Signal acceptance in SR-HM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. 1lb\bar{b}$ production
Signal acceptance in SR-HM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. 1lb\bar{b}$ production
Signal acceptance in SR-HM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-HM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-HM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-HM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-HM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-HM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-HM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-HM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-HM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-HM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-HM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-HM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-LM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-LM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-LM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-LM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-LM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-LM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-LM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-LM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-LM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-LM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-LM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-LM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-LM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-LM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-LM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-LM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-MM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-MM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-MM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-MM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-MM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-MM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-MM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-MM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-MM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-MM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-MM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-MM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-MM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-MM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-MM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-HM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-HM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-HM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-HM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-HM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-HM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-HM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-HM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-HM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-HM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-HM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-HM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-HM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-HM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Event selection cutflow for a representative signal sample for the SR-LM low $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-LM low $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-LM low $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-LM low $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-LM med. $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-LM med. $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-LM med. $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-LM med. $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-LM high $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-LM high $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-LM high $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-MM low $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-MM low $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-MM low $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-MM low $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-MM med. $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-MM med. $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-MM med. $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-MM med. $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-MM high $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-MM high $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-MM high $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-MM high $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-HM low $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-HM low $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-HM low $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-HM low $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-HM med. $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-HM med. $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-HM med. $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-HM med. $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-HM high $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-HM high $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-HM high $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-HM high $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the discovery SR-LM. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the discovery SR-LM. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the discovery SR-LM. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the discovery SR-LM. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the discovery SR-MM. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the discovery SR-MM. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the discovery SR-MM. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the discovery SR-MM. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the discovery SR-HM. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the discovery SR-HM. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the discovery SR-HM. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the discovery SR-HM. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
The result of a search for the pair production of the lightest supersymmetric partner of the bottom quark ($\tilde{b}_{1}$) using 139 fb$^{-1}$ of proton-proton data collected at $\sqrt{s} = 13$ TeV by the ATLAS detector is reported. In the supersymmetric scenarios considered both of the bottom-squarks decay into a $b$-quark and the second-lightest neutralino, $\tilde{b}_{1} \rightarrow b + \tilde{\chi}^{0}_{2}$. Each $\tilde{\chi}^{0}_{2}$ is assumed to subsequently decay with 100% branching ratio into a Higgs boson ($h$) like the one in the Standard Model and the lightest neutralino: $\tilde{\chi}^{0}_{2} \rightarrow h + \tilde{\chi}^{0}_{1}$. The $\tilde{\chi}^{0}_{1}$ is assumed to be the lightest supersymmetric particle (LSP) and is stable. Two signal mass configurations are targeted: the first has a constant LSP mass of 60 GeV; and the second has a constant mass difference between the $\tilde{\chi}^{0}_{2}$ and $\tilde{\chi}^{0}_{1}$ of 130 GeV. The final states considered contain no charged leptons, three or more $b$-jets, and large missing transverse momentum. No significant excess of events over the Standard Model background expectation is observed in any of the signal regions considered. Limits at the 95% confidence level are placed in the supersymmetric models considered, and bottom-squarks with mass up to 1.5 TeV are excluded.
Distributions of ${E}_{\mathrm{T}}^{\mathrm{miss}}$ after the background-only fit. The backgrounds which contribute only a small amount (diboson, W+jets and ttbar+W/Z/h) are grouped and labelled as `Other'.
Distributions of ${E}_{\mathrm{T}}^{\mathrm{miss}}$ after the background-only fit. The backgrounds which contribute only a small amount (diboson, W+jets and ttbar+W/Z/h) are grouped and labelled as `Other'.
Distributions of $m_{\mathrm{eff}}$ after the background-only fit. The backgrounds which contribute only a small amount (diboson, W+jets and ttbar+W/Z/h) are grouped and labelled as `Other'.
Distributions of $m_{\mathrm{eff}}$ after the background-only fit. The backgrounds which contribute only a small amount (diboson, W+jets and ttbar+W/Z/h) are grouped and labelled as `Other'.
Distributions of Object-based $E_{\mathrm{T}}^{\mathrm{miss}} {Sig.}$ after the background-only fit. The backgrounds which contribute only a small amount (diboson, W+jets and ttbar+W/Z/h) are grouped and labelled as `Other'.
Distributions of Object-based $E_{\mathrm{T}}^{\mathrm{miss}} {Sig.}$ after the background-only fit. The backgrounds which contribute only a small amount (diboson, W+jets and ttbar+W/Z/h) are grouped and labelled as `Other'.
Distributions of MaxMin alternative algorithm $m(h_{\mathrm{cand1}},h_{\mathrm{cand2}})_{\mathrm{avg}}$ after the background-only fit. The backgrounds which contribute only a small amount (diboson, W+jets and ttbar+W/Z/h) are grouped and labelled as `Other'.
Distributions of MaxMin alternative algorithm $m(h_{\mathrm{cand1}},h_{\mathrm{cand2}})_{\mathrm{avg}}$ after the background-only fit. The backgrounds which contribute only a small amount (diboson, W+jets and ttbar+W/Z/h) are grouped and labelled as `Other'.
Distributions of Leading jet $p_T$ after the background-only fit. The backgrounds which contribute only a small amount (diboson, W+jets and ttbar+W/Z/h) are grouped and labelled as `Other'.
Distributions of Leading jet $p_T$ after the background-only fit. The backgrounds which contribute only a small amount (diboson, W+jets and ttbar+W/Z/h) are grouped and labelled as `Other'.
Distributions of MaxMin algorithm $m_{hcand}$ after the background-only fit. The backgrounds which contribute only a small amount (diboson, W+jets and ttbar+W/Z/h) are grouped and labelled as `Other'.
Distributions of MaxMin algorithm $m_{hcand}$ after the background-only fit. The backgrounds which contribute only a small amount (diboson, W+jets and ttbar+W/Z/h) are grouped and labelled as `Other'.
Signal efficiency in SRA_M_m60 for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal efficiency in SRA_M_m60 for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal acceptance in SRC_28 for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal acceptance in SRC_28 for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal acceptance in SRC_26 for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal acceptance in SRC_26 for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal acceptance in SRC_24 for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal acceptance in SRC_24 for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal acceptance in SRA_M_dm130 for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal acceptance in SRA_M_dm130 for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal acceptance in SRB for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal acceptance in SRB for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal acceptance in SRA_L_dm130 for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal acceptance in SRA_L_dm130 for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal acceptance in SRC_incl for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal acceptance in SRC_incl for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal acceptance in SRA_L_m60 for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal acceptance in SRA_L_m60 for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal acceptance in SRA_incl_dm130 for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal acceptance in SRA_incl_dm130 for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal acceptance in SRA_incl_m60 for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal acceptance in SRA_incl_m60 for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal efficiency in SRA_H_m60 for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal efficiency in SRA_H_m60 for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal efficiency in SRA_L_dm130 for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal efficiency in SRA_L_dm130 for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal efficiency in SRB for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal efficiency in SRB for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal acceptance in SRC_22 for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal acceptance in SRC_22 for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal efficiency in SRA_H_dm130 for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal efficiency in SRA_H_dm130 for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal efficiency in SRC_24 for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal efficiency in SRC_24 for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal efficiency in SRC_26 for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal efficiency in SRC_26 for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal acceptance in SRA_H_m60 for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal acceptance in SRA_H_m60 for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal efficiency in SRA_incl_m60 for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal efficiency in SRA_incl_m60 for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal efficiency in SRC_22 for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal efficiency in SRC_22 for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal acceptance in SRA_M_m60 for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal acceptance in SRA_M_m60 for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal efficiency in SRC_28 for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal efficiency in SRC_28 for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal acceptance in SRA_H_dm130 for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal acceptance in SRA_H_dm130 for simplified models with $\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$ production
Signal efficiency in SRA_incl_dm130 for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal efficiency in SRA_incl_dm130 for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal efficiency in SRA_L_m60 for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal efficiency in SRA_L_m60 for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal efficiency in SRA_M_dm130 for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal efficiency in SRA_M_dm130 for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal efficiency in SRC_incl for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Signal efficiency in SRC_incl for simplified models with '$\widetilde{b}\widetilde{b}$ $\rightarrow$ $b\bar{b} \widetilde{\chi}_2^0 \widetilde{\chi}_2^0$ $\rightarrow$ hh$\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$, h $\rightarrow$ $b\bar{b}$' production
Observed 95% CLs exclusion limit for the $\Delta M(\widetilde{\chi}_{2}^{0},\widetilde{\chi}_{1}^{0})$=130GeV signal grid for the best combined signal regions.
Observed 95% CLs exclusion limit for the $\Delta M(\widetilde{\chi}_{2}^{0},\widetilde{\chi}_{1}^{0})$=130GeV signal grid for the best combined signal regions.
Expected 95% CLs exclusion limit for the $\Delta M(\widetilde{\chi}_{2}^{0},\widetilde{\chi}_{1}^{0})$=130GeV signal grid for the best combined signal regions.
Expected 95% CLs exclusion limit for the $\Delta M(\widetilde{\chi}_{2}^{0},\widetilde{\chi}_{1}^{0})$=130GeV signal grid for the best combined signal regions.
Observed 95% CLs exclusion limit for the $M(\widetilde{\chi}_{1}^{0})$=60GeV signal grid for the best combined signal regions.
Observed 95% CLs exclusion limit for the $M(\widetilde{\chi}_{1}^{0})$=60GeV signal grid for the best combined signal regions.
Expected 95% CLs exclusion limit for the $\Delta M(\widetilde{\chi}_{2}^{0},\widetilde{\chi}_{1}^{0})$=130GeV signal grid for the best combined signal regions.
Expected 95% CLs exclusion limit for the $M(\widetilde{\chi}_{1}^{0})$=60GeV signal grid for the best combined signal regions.
Model dependent upper limit on the best combined signal regions considered in the $\Delta M(\widetilde{\chi}_{2}^{0},\widetilde{\chi}_{1}^{0})$=130GeV signal grid
Model dependent upper limit on the best combined signal regions considered in the $\Delta M(\widetilde{\chi}_{2}^{0},\widetilde{\chi}_{1}^{0})$=130GeV signal grid
Model dependet upper limits on the best combined signal regions considered in the $\Delta M(\widetilde{\chi}_{2}^{0},\widetilde{\chi}_{1}^{0})$=130GeV signal grid
Model dependet upper limits on the best combined signal regions considered in the $\Delta M(\widetilde{\chi}_{2}^{0},\widetilde{\chi}_{1}^{0})$=130GeV signal grid
Result of background only fit applied to signal regions. Event yields from the signal regions compared with SM MC predictions for the 3 highest contributing backgrounds separately and combined minor backgrounds.
Result of background only fit applied to signal regions. Event yields from the signal regions compared with SM MC predictions for the 3 highest contributing backgrounds separately and combined minor backgrounds.
Expected background event yields and dominant systematic uncertainties on background estimates in the A-type (inclusive), B-type and C-type (inclusive) regions.
Expected background event yields and dominant systematic uncertainties on background estimates in the A-type (inclusive), B-type and C-type (inclusive) regions.
Background-only fit results for the A- and B-type regions performed using 139$fb^{-1}$ of data. The quoted uncertainties on the fitted SM background include both the statistical and systematic uncertainties.
Background-only fit results for the A- and B-type regions performed using 139$fb^{-1}$ of data. The quoted uncertainties on the fitted SM background include both the statistical and systematic uncertainties.
Background-only fit results for the C-type region performed using 139$fb^{-1}$ of data. The quoted uncertainties on the fitted SM background include both the statistical and systematic uncertainties.
Background-only fit results for the C-type region performed using 139$fb^{-1}$ of data. The quoted uncertainties on the fitted SM background include both the statistical and systematic uncertainties.
Observed 95% CL upper limits on the visible cross sections σvis, the observed (S95obs) and expected (S95exp) 95% CL upper limits on the number of signal events with ± 1 σ excursions of the expectation, the CL of the background-only hypothesis, CLB, the discovery p-value (p0), truncated at 0.5, and the associated significance.
Observed 95% CL upper limits on the visible cross sections σvis, the observed (S95obs) and expected (S95exp) 95% CL upper limits on the number of signal events with ± 1 σ excursions of the expectation, the CL of the background-only hypothesis, CLB, the discovery p-value (p0), truncated at 0.5, and the associated significance.
Cutflow of the MC events scaled to 139 $fb^{-1}$ for the SRA selections, with a scalar bottom signal of m$(\widetilde{b}_{1},\widetilde{\chi}_2^0,\widetilde{\chi}_1^0) = (1100, 330, 200)$ GeV, considered.
Cutflow of the MC events scaled to 139 $fb^{-1}$ for the SRA selections, with a scalar bottom signal of m$(\widetilde{b}_{1},\widetilde{\chi}_2^0,\widetilde{\chi}_1^0) = (1100, 330, 200)$ GeV, considered.
Cutflow of the MC events scaled to 139 $fb^{-1}$ for the SRB selections, with a scalar bottom signal of m$(\widetilde{b}_{1},\widetilde{\chi}_2^0,\widetilde{\chi}_1^0) = (700, 680, 550)$ GeV, considered.
Cutflow of the MC events scaled to 139 $fb^{-1}$ for the SRB selections, with a scalar bottom signal of m$(\widetilde{b}_{1},\widetilde{\chi}_2^0,\widetilde{\chi}_1^0) = (700, 680, 550)$ GeV, considered.
Cutflow of the MC events scaled to 139 $fb^{-1}$ for the SRC selections, with a scalar bottom signal of m$(\widetilde{b}_{1},\widetilde{\chi}_2^0,\widetilde{\chi}_1^0) = (1200, 1150, 60)$ GeV, considered.
Cutflow of the MC events scaled to 139 $fb^{-1}$ for the SRC selections, with a scalar bottom signal of m$(\widetilde{b}_{1},\widetilde{\chi}_2^0,\widetilde{\chi}_1^0) = (1200, 1150, 60)$ GeV, considered.
A search for direct pair production of scalar partners of the top quark (top squarks or scalar third-generation up-type leptoquarks) in the all-hadronic $t\bar{t}$ plus missing transverse momentum final state is presented. The analysis of 139 fb$^{-1}$ of ${\sqrt{s}=13}$ TeV proton-proton collision data collected using the ATLAS detector at the LHC yields no significant excess over the Standard Model background expectation. To interpret the results, a supersymmetric model is used where the top squark decays via $\tilde{t} \to t^{(*)} \tilde{\chi}^0_1$, with $t^{(*)}$ denoting an on-shell (off-shell) top quark and $\tilde{\chi}^0_1$ the lightest neutralino. Three specific event selections are optimised for the following scenarios. In the scenario where $m_{\tilde{t}}> m_t+m_{\tilde{\chi}^0_1}$, top squark masses are excluded in the range 400-1250 GeV for $\tilde{\chi}^0_1$ masses below $200$ GeV at 95 % confidence level. In the situation where $m_{\tilde{t}}\sim m_t+m_{\tilde{\chi}^0_1}$, top squark masses in the range 300-630 GeV are excluded, while in the case where $m_{\tilde{t}}< m_W+m_b+m_{\tilde{\chi}^0_1}$ (with $m_{\tilde{t}}-m_{\tilde{\chi}^0_1}\ge 5$ GeV), considered for the first time in an ATLAS all-hadronic search, top squark masses in the range 300-660 GeV are excluded. Limits are also set for scalar third-generation up-type leptoquarks, excluding leptoquarks with masses below $1240$ GeV when considering only leptoquark decays into a top quark and a neutrino.
<b>- - - - - - - - Overview of HEPData Record - - - - - - - -</b> <br><br> <b>Exclusion contours:</b> <ul> <li><a href="?table=stop_obs">Stop exclusion contour (Obs.)</a> <li><a href="?table=stop_obs_down">Stop exclusion contour (Obs. Down)</a> <li><a href="?table=stop_obs_up">Stop exclusion contour (Obs. Up)</a> <li><a href="?table=stop_exp">Stop exclusion contour (Exp.)</a> <li><a href="?table=stop_exp_down">Stop exclusion contour (Exp. Down)</a> <li><a href="?table=stop_exp_up">Stop exclusion contour (Exp. Up)</a> <li><a href="?table=LQ3u_obs">LQ3u exclusion contour (Obs.)</a> <li><a href="?table=LQ3u_obs_down">LQ3u exclusion contour (Obs. Down)</a> <li><a href="?table=LQ3u_obs_up">LQ3u exclusion contour (Obs. Up)</a> <li><a href="?table=LQ3u_exp">LQ3u exclusion contour (Exp.)</a> <li><a href="?table=LQ3u_exp_down">LQ3u exclusion contour (Exp. Down)</a> <li><a href="?table=LQ3u_exp_up">LQ3u exclusion contour (Exp. Up)</a> </ul> <b>Upper limits:</b> <ul> <li><a href="?table=stop_xSecUpperLimit_obs">stop_xSecUpperLimit_obs</a> <li><a href="?table=stop_xSecUpperLimit_exp">stop_xSecUpperLimit_exp</a> <li><a href="?table=LQ3u_xSecUpperLimit_obs">LQ3u_xSecUpperLimit_obs</a> <li><a href="?table=LQ3u_xSecUpperLimit_exp">LQ3u_xSecUpperLimit_exp</a> </ul> <b>Kinematic distributions:</b> <ul> <li><a href="?table=SRATW_metsigST">SRATW_metsigST</a> <li><a href="?table=SRBTT_m_1fatjet_kt12">SRBTT_m_1fatjet_kt12</a> <li><a href="?table=SRC_RISR">SRC_RISR</a> <li><a href="?table=SRD0_htSig">SRD0_htSig</a> <li><a href="?table=SRD1_htSig">SRD1_htSig</a> <li><a href="?table=SRD2_htSig">SRD2_htSig</a> </ul> <b>Cut flows:</b> <ul> <li><a href="?table=cutflow_SRATT">cutflow_SRATT</a> <li><a href="?table=cutflow_SRATW">cutflow_SRATW</a> <li><a href="?table=cutflow_SRAT0">cutflow_SRAT0</a> <li><a href="?table=cutflow_SRB">cutflow_SRB</a> <li><a href="?table=cutflow_SRC">cutflow_SRC</a> <li><a href="?table=cutflow_SRD0">cutflow_SRD0</a> <li><a href="?table=cutflow_SRD1">cutflow_SRD1</a> <li><a href="?table=cutflow_SRD2">cutflow_SRD2</a> </ul> <b>Acceptance and efficiencies:</b> As explained in <a href="https://twiki.cern.ch/twiki/bin/view/AtlasPublic/SupersymmetryPublicResults#summary_of_auxiliary_material">the twiki</a>. <ul> <li> <b>SRATT:</b> <a href="?table=Acc_SRATT">Acc_SRATT</a> <a href="?table=Eff_SRATT">Eff_SRATT</a> <li> <b>SRATW:</b> <a href="?table=Acc_SRATW">Acc_SRATW</a> <a href="?table=Eff_SRATW">Eff_SRATW</a> <li> <b>SRAT0:</b> <a href="?table=Acc_SRAT0">Acc_SRAT0</a> <a href="?table=Eff_SRAT0">Eff_SRAT0</a> <li> <b>SRBTT:</b> <a href="?table=Acc_SRBTT">Acc_SRBTT</a> <a href="?table=Eff_SRBTT">Eff_SRBTT</a> <li> <b>SRBTW:</b> <a href="?table=Acc_SRBTW">Acc_SRBTW</a> <a href="?table=Eff_SRBTW">Eff_SRBTW</a> <li> <b>SRBT0:</b> <a href="?table=Acc_SRBT0">Acc_SRBT0</a> <a href="?table=Eff_SRBT0">Eff_SRBT0</a> <li> <b>SRC1:</b> <a href="?table=Acc_SRC1">Acc_SRC1</a> <a href="?table=Eff_SRC1">Eff_SRC1</a> <li> <b>SRC2:</b> <a href="?table=Acc_SRC2">Acc_SRC2</a> <a href="?table=Eff_SRC2">Eff_SRC2</a> <li> <b>SRC3:</b> <a href="?table=Acc_SRC3">Acc_SRC3</a> <a href="?table=Eff_SRC3">Eff_SRC3</a> <li> <b>SRC4:</b> <a href="?table=Acc_SRC4">Acc_SRC4</a> <a href="?table=Eff_SRC4">Eff_SRC4</a> <li> <b>SRC5:</b> <a href="?table=Acc_SRC5">Acc_SRC5</a> <a href="?table=Eff_SRC5">Eff_SRC5</a> <li> <b>SRD0:</b> <a href="?table=Acc_SRD0">Acc_SRD0</a> <a href="?table=Eff_SRD0">Eff_SRD0</a> <li> <b>SRD1:</b> <a href="?table=Acc_SRD1">Acc_SRD1</a> <a href="?table=Eff_SRD1">Eff_SRD1</a> <li> <b>SRD2:</b> <a href="?table=Acc_SRD2">Acc_SRD2</a> <a href="?table=Eff_SRD2">Eff_SRD2</a> </ul> <b>Truth Code snippets</b> and <b>SLHA</a> files are available under "Resources" (purple button on the left)
The observed exclusion contour at 95% CL as a function of the $\it{m}_{\tilde{\chi}^{0}_{1}}$ vs. $\it{m}_{\tilde{t}}$. Masses that are within the contours are excluded.
The expected exclusion contour at 95% CL as a function of the $\it{m}_{\tilde{\chi}^{0}_{1}}$ vs. $\it{m}_{\tilde{t}}$. Masses that are within the contour are excluded.
The minus $1\sigma$ variation of observed exclusion contour obtained by varying the signal cross section within its uncertainty. The contour is given as a function of the $\it{m}_{\tilde{\chi}^{0}_{1}}$ vs. $\it{m}_{\tilde{t}}$.
The plus $1\sigma$ variation of observed exclusion contour obtained by varying the signal cross section within its uncertainty. The contour is given as a function of the $\it{m}_{\tilde{\chi}^{0}_{1}}$ vs. $\it{m}_{\tilde{t}}$.
The minus $1\sigma$ variation of expected exclusion contour obtained by varying MC statistical uncertainties, detector-related systematic uncertainties, and theoretical uncertainties (excluding signal cross section uncertainties). The contour is given as a function of the $\it{m}_{\tilde{\chi}^{0}_{1}}$ vs. $\it{m}_{\tilde{t}}$.
The plus $1\sigma$ variation of expected exclusion contour obtained by varying MC statistical uncertainties, detector-related systematic uncertainties, and theoretical uncertainties (excluding signal cross section uncertainties). The contour is given as a function of the $\it{m}_{\tilde{\chi}^{0}_{1}}$ vs. $\it{m}_{\tilde{t}}$.
The observed exclusion contour at 95% CL as a function of the $\it{m}_{LQ_{3}^{u}}$ vs. $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau)$. Points that are within the contours are excluded.
The expected exclusion contour at 95% CL as a function of the $\it{m}_{LQ_{3}^{u}}$ vs. $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau)$. Points that are within the contours are excluded.
The minus $1\sigma$ variation of observed exclusion contour obtained by varying the signal cross section within its uncertainty. The contour is given as a function of the $\it{m}_{LQ_{3}^{u}}$ vs. $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau)$
The plus $1\sigma$ variation of observed exclusion contour obtained by varying the signal cross section within its uncertainty. The contour is given as a function of the $\it{m}_{LQ_{3}^{u}}$ vs. $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau)$
The plus $1\sigma$ variation of expected exclusion contour obtained by varying MC statistical uncertainties, detector-related systematic uncertainties, and theoretical uncertainties (excluding signal cross section uncertainties). The contour is given as a function of the $\it{m}_{LQ_{3}^{u}}$ vs. $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau)$
The minus $1\sigma$ variation of expected exclusion contour obtained by varying MC statistical uncertainties, detector-related systematic uncertainties, and theoretical uncertainties (excluding signal cross section uncertainties). The contour is given as a function of the $\it{m}_{LQ_{3}^{u}}$ vs. $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau)$
Model dependent upper limit on the cross section for the $(\tilde{t},\tilde{\chi}^{0}_{1})$ signal grid. The column titled 'Leading Region' stores information on which of the fit regions (SRA-B, SRC or SRD) is the dominant based on the expected CLs values.
Expected model dependent upper limit on the cross section for the $(\tilde{t},\tilde{\chi}^{0}_{1})$ signal grid. The column titled 'Leading Region' stores information on which of the fit regions (SRA-B, SRC or SRD) is the dominant based on the expected CLs values.
Model dependent upper limit on the cross section for the $LQ_{3}^{u}$ signal grid with $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau))=0$ %. Only the SRA-B fit region is considered in this interpretation.
Expected model dependent upper limit on the cross section for the $LQ_{3}^{u}$ signal grid with $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau))=0$ %. Only the SRA-B fit region is considered in this interpretation.
The distributions of $S$ in SRA-TW. For each bin yields for the data, total SM prediction and a representative signal point are provided. The SM prediction is provided with the MC statistical uncertainties, labeled 'stat', and the remaining uncertainties, labeled 'syst' that include detector-related systematic uncertainties and theoretical uncertainties. The signal predictions is provided with the MC statistical uncertainties only. The rightmost bin includes overflow events.
The distributions of $\it{m}^{\mathrm{R=1.2}}_{1}$ in SRB-TT. For each bin yields for the data, total SM prediction and a representative signal point are provided. The SM prediction is provided with the MC statistical uncertainties, labeled 'stat', and the remaining uncertainties, labeled 'syst' that include detector-related systematic uncertainties and theoretical uncertainties. The signal predictions is provided with the MC statistical uncertainties only. The rightmost bin includes overflow events.
The distributions of R$_{ISR}$ in SRC signal regions before R$_{ISR}$ cuts are applied. For each bin yields for the data, total SM prediction and a representative signal point are provided. The SM prediction is provided with the MC statistical uncertainties, labeled 'stat', and the remaining uncertainties, labeled 'syst' that include detector-related systematic uncertainties and theoretical uncertainties. The signal predictions is provided with the MC statistical uncertainties only. The rightmost bin includes overflow events.
The distributions of $E^{miss}_{T}/\sqrt{H_{T}}$ in SRD0. For each bin yields for the data, total SM prediction and a representative signal point are provided. The SM prediction is provided with the MC statistical uncertainties, labeled 'stat', and the remaining uncertainties, labeled 'syst' that include detector-related systematic uncertainties and theoretical uncertainties. The signal predictions is provided with the MC statistical uncertainties only. The rightmost bin includes overflow events.
The distributions of $E^{miss}_{T}/\sqrt{H_{T}}$ in SRD1. For each bin yields for the data, total SM prediction and a representative signal point are provided. The SM prediction is provided with the MC statistical uncertainties, labeled 'stat', and the remaining uncertainties, labeled 'syst' that include detector-related systematic uncertainties and theoretical uncertainties. The signal predictions is provided with the MC statistical uncertainties only. The rightmost bin includes overflow events.
The distributions of $E^{miss}_{T}/\sqrt{H_{T}}$ in SRD2. For each bin yields for the data, total SM prediction and a representative signal point are provided. The SM prediction is provided with the MC statistical uncertainties, labeled 'stat', and the remaining uncertainties, labeled 'syst' that include detector-related systematic uncertainties and theoretical uncertainties. The signal predictions is provided with the MC statistical uncertainties only. The rightmost bin includes overflow events.
Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (1300,1)\ \mathrm{GeV} $ in SRA-TT. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 30000 raw MC events were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.
Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (1300,1)\ \mathrm{GeV} $ in SRA-TW. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 30000 raw MC events were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.
Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (1300,1)\ \mathrm{GeV} $ in SRA-T0. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 30000 raw MC events were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.
Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (700,400)\ \mathrm{GeV} $ in signal regions SRB-TT, SRB-TW and SRB-T0. The regions differ by the last cut applied. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 60000 raw MC events were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.
Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (500,327)\ \mathrm{GeV} $ in regions SRC-1, SRC-2, SRC-3, SRC-4 and SRC-5. The regions differ by the last cut applied. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 150000 raw MC events with filter efficiency of 0.384 were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.
Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (550,500)\ \mathrm{GeV} $ in SRD0. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 90000 raw MC events with filter efficiency of 0.428 were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.
Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (550,500)\ \mathrm{GeV} $ in SRD1. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 90000 raw MC events with filter efficiency of 0.428 were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.
Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (550,500)\ \mathrm{GeV} $ in SRD2. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 90000 raw MC events with filter efficiency of 0.428 were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.
Signal acceptance in SRA-TT for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$
Signal efficiency in SRA-TT for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in %.
Signal acceptance in SRA-TW for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$
Signal efficiency in SRA-TW for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in %.
Signal acceptance in SRA-T0 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$
Signal efficiency in SRA-T0 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in %.
Signal acceptance in SRB-TT for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$
Signal efficiency in SRB-TT for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in %.
Signal acceptance in SRB-TW for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$
Signal efficiency in SRB-TW for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in %.
Signal acceptance in SRB-T0 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$
Signal efficiency in SRB-T0 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in %.
Signal acceptance in SRC1 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal efficiency in SRC1 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal acceptance in SRC2 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal efficiency in SRC2 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal acceptance in SRC3 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal efficiency in SRC3 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal acceptance in SRC4 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal efficiency in SRC4 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ plane showed in the paper plot.
Signal acceptance in SRC5 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ plane showed in the paper plot.
Signal efficiency in SRC5 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal acceptance in SRD0 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal efficiency in SRD0 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal acceptance in SRD1 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal efficiency in SRD1 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal acceptance in SRD2 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal efficiency in SRD2 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
A search for supersymmetric partners of gluons and quarks is presented, involving signatures with jets and either two isolated leptons (electrons or muons) with the same electric charge, or at least three isolated leptons. A data sample of proton-proton collisions at $\sqrt{s}$ = 13 TeV recorded with the ATLAS detector at the Large Hadron Collider between 2015 and 2018, corresponding to a total integrated luminosity of 139 fb$^{-1}$, is used for the search. No significant excess over the Standard Model expectation is observed. The results are interpreted in simplified supersymmetric models featuring both R-parity conservation and R-parity violation, raising the exclusion limits beyond those of previous ATLAS searches to 1600 GeV for gluino masses and 750 GeV for bottom and top squark masses in these scenarios.
Observed 95% CL exclusion contours in signal region Rpc2L0b on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g \to q \bar{q}^{'} \tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm \to W^\pm \tilde{\chi}_2^0$ and $ \tilde{\chi}_2^0 \to Z \tilde{\chi}_1^0$.
Observed 95% CL exclusion contours in signal region Rpc2L0b on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g \to q \bar{q}^{'} \tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm \to W^\pm \tilde{\chi}_2^0$ and $ \tilde{\chi}_2^0 \to Z \tilde{\chi}_1^0$.
Observed 95% CL exclusion contours in signal region Rpc2L0b on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g \to q \bar{q}^{'} \tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm \to W^\pm \tilde{\chi}_2^0$ and $ \tilde{\chi}_2^0 \to Z \tilde{\chi}_1^0$.
Expected 95% CL exclusion contours in signal region Rpc2L0b on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.
Expected 95% CL exclusion contours in signal region Rpc2L0b on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.
Expected 95% CL exclusion contours in signal region Rpc2L0b on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.
Observed 95% CL exclusion contours in signal region Rpv2L on the gluino and lightest top squark masses in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Observed 95% CL exclusion contours in signal region Rpv2L on the gluino and lightest top squark masses in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Observed 95% CL exclusion contours in signal region Rpv2L on the gluino and lightest top squark masses in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Expected 95% CL exclusion contours in signal region Rpv2L on the gluino and lightest top squark masses in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Expected 95% CL exclusion contours in signal region Rpv2L on the gluino and lightest top squark masses in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Expected 95% CL exclusion contours in signal region Rpv2L on the gluino and lightest top squark masses in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Observed 95% CL exclusion contours in the best combination of signal regions of Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Observed 95% CL exclusion contours in the best combination of signal regions of Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Observed 95% CL exclusion contours in the best combination of signal regions of Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Expected 95% CL exclusion contours in the best combination of signal regions of Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Expected 95% CL exclusion contours in the best combination of signal regions of Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Expected 95% CL exclusion contours in the best combination of signal regions of Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L0b, in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1600 GeV, $m(\tilde \chi_1^\pm)$ = 1200 GeV, $m(\tilde \chi_2^0)$ = 1000 GeV and $m(\tilde \chi_1^0)$ = 800 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L0b, in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1600 GeV, $m(\tilde \chi_1^\pm)$ = 1200 GeV, $m(\tilde \chi_2^0)$ = 1000 GeV and $m(\tilde \chi_1^0)$ = 800 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L0b, in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1600 GeV, $m(\tilde \chi_1^\pm)$ = 1200 GeV, $m(\tilde \chi_2^0)$ = 1000 GeV and $m(\tilde \chi_1^0)$ = 800 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L1b, in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde{b}^{}_1)$ = 850 GeV, $m(\tilde \chi_1^\pm)$ = 500 GeV and $m(\tilde \chi_1^0)$ = 400 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L1b, in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde{b}^{}_1)$ = 850 GeV, $m(\tilde \chi_1^\pm)$ = 500 GeV and $m(\tilde \chi_1^0)$ = 400 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L1b, in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde{b}^{}_1)$ = 850 GeV, $m(\tilde \chi_1^\pm)$ = 500 GeV and $m(\tilde \chi_1^0)$ = 400 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L2b, in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde{b}^{}_1)$ = 850 GeV, $m(\tilde \chi_1^\pm)$ = 500 GeV and $m(\tilde \chi_1^0)$ = 400 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L2b, in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde{b}^{}_1)$ = 900 GeV, $m(\tilde \chi_1^\pm)$ = 150 GeV and $m(\tilde \chi_1^0)$ = 50 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L2b, in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde{b}^{}_1)$ = 900 GeV, $m(\tilde \chi_1^\pm)$ = 150 GeV and $m(\tilde \chi_1^0)$ = 50 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc3LSS1b, in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate. The masses of the superpartners involved in the process are set to $m(\tilde{t}^{}_1)$ = 800 GeV, $m(\tilde \chi_2^0)$ = 625 GeV, $m(\tilde \chi_1^\pm)\approx m(\tilde \chi_1^0)$ = 525 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc3LSS1b, in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate. The masses of the superpartners involved in the process are set to $m(\tilde{t}^{}_1)$ = 800 GeV, $m(\tilde \chi_2^0)$ = 625 GeV, $m(\tilde \chi_1^\pm)\approx m(\tilde \chi_1^0)$ = 525 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc3LSS1b, in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate. The masses of the superpartners involved in the process are set to $m(\tilde{t}^{}_1)$ = 800 GeV, $m(\tilde \chi_2^0)$ = 625 GeV, $m(\tilde \chi_1^\pm)\approx m(\tilde \chi_1^0)$ = 525 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpv2L, in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1600 GeV, $m(\tilde{t}^{}_{1})$ = 800 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpv2L, in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1600 GeV, $m(\tilde{t}^{}_{1})$ = 800 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpv2L, in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1600 GeV, $m(\tilde{t}^{}_{1})$ = 800 GeV. Only statistical uncertainties are shown.
Signal acceptance for Rpc2L0b signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.
Signal acceptance for Rpc2L0b signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.
Signal acceptance for Rpc2L0b signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.
Signal acceptance for Rpc2L1b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Signal acceptance for Rpc2L1b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Signal acceptance for Rpc2L1b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Signal acceptance for Rpc2L2b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Signal acceptance for Rpc2L2b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Signal acceptance for Rpc2L2b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Signal acceptance for Rpv2L signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Signal acceptance for Rpv2L signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Signal acceptance for Rpv2L signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Signal acceptance for Rpc3LSS1b signal region with sensitivity to $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.
Signal acceptance for Rpc3LSS1b signal region with sensitivity to $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.
Signal acceptance for Rpc3LSS1b signal region with sensitivity to $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.
Signal efficiency for Rpc2L0b signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.
Signal efficiency for Rpc2L0b signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.
Signal efficiency for Rpc2L0b signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.
Signal efficiency for Rpc2L1b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Signal efficiency for Rpc2L1b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Signal efficiency for Rpc2L1b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Signal efficiency for Rpc2L2b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Signal efficiency for Rpc2L2b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Signal efficiency for Rpc2L2b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Signal efficiency for Rpv2L signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Signal efficiency for Rpv2L signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Signal efficiency for Rpv2L signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Signal efficiency for Rpc3LSS1b signal region with sensitivity to $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.
Signal efficiency for Rpc3LSS1b signal region with sensitivity to $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.
Signal efficiency for Rpc3LSS1b signal region with sensitivity to $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.
Observed 95% CL upper limit on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.
Observed 95% CL upper limit on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.
Observed 95% CL upper limit on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.
Observed 95% CL upper limit on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Observed 95% CL upper limit on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Observed 95% CL upper limit on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Observed 95% CL upper limit on $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Observed 95% CL upper limit on $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Observed 95% CL upper limit on $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Observed 95% CL upper limit on $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.
Observed 95% CL upper limit on $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.
Observed 95% CL upper limit on $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.
Best observed 95% CL exclusion contours selected from Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Best observed 95% CL exclusion contours selected from Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Best observed 95% CL exclusion contours selected from Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}}$ of observed data and expected background towards Rpc2L0b from publication's Figure 5 . The last bin is inclusive.
N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}}$ of observed data and expected background towards Rpc2L0b from publication's Figure 5 . The last bin is inclusive.
N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}}$ of observed data and expected background towards Rpc2L0b from publication's Figure 5 . The last bin is inclusive.
N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}} / m_{\mathrm{eff}}$ of observed data and expected background towards Rpc2L1b from publication's Figure 5 . The last bin is inclusive.
N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}} / m_{\mathrm{eff}}$ of observed data and expected background towards Rpc2L1b from publication's Figure 5 . The last bin is inclusive.
N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}} / m_{\mathrm{eff}}$ of observed data and expected background towards Rpc2L1b from publication's Figure 5 . The last bin is inclusive.
N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}}$ of observed data and expected background towards Rpc2L2b from publication's Figure 5 . The last bin is inclusive.
N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}}$ of observed data and expected background towards Rpc2L2b from publication's Figure 5 . The last bin is inclusive.
N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}}$ of observed data and expected background towards Rpc2L2b from publication's Figure 5 . The last bin is inclusive.
N-1 distributions for $m_{\mathrm{eff}}$ of observed data and expected background towards Rpv2L from publication's Figure 5 . The last bin is inclusive.
N-1 distributions for $m_{\mathrm{eff}}$ of observed data and expected background towards Rpv2L from publication's Figure 5 . The last bin is inclusive.
N-1 distributions for $m_{\mathrm{eff}}$ of observed data and expected background towards Rpv2L from publication's Figure 5 . The last bin is inclusive.
A search for electroweak production of supersymmetric particles in scenarios with compressed mass spectra in final states with two low-momentum leptons and missing transverse momentum is presented. This search uses proton-proton collision data recorded by the ATLAS detector at the Large Hadron Collider in 2015-2016, corresponding to 36.1 fb$^{-1}$ of integrated luminosity at $\sqrt{s}=13$ TeV. Events with same-flavor pairs of electrons or muons with opposite electric charge are selected. The data are found to be consistent with the Standard Model prediction. Results are interpreted using simplified models of R-parity-conserving supersymmetry in which there is a small mass difference between the masses of the produced supersymmetric particles and the lightest neutralino. Exclusion limits at 95% confidence level are set on next-to-lightest neutralino masses of up to 145 GeV for Higgsino production and 175 GeV for wino production, and slepton masses of up to 190 GeV for pair production of sleptons. In the compressed mass regime, the exclusion limits extend down to mass splittings of 2.5 GeV for Higgsino production, 2 GeV for wino production, and 1 GeV for slepton production. The results are also interpreted in the context of a radiatively-driven natural supersymmetry model with non-universal Higgs boson masses.
<b>Kinematics 1</b> Kinematic distributions after the background-only fit showing the data as well as the expected background in the inclusive electroweakino SRℓℓ-m<sub>ℓℓ</sub> [1, 60] (top) and slepton SRℓℓ-m<sub>T2</sub><sup>100</sup> [100, ∞] (bottom) signal regions. The arrow in the E<sub>T</sub><sup>miss</sup>/H<sub>T</sub><sup>lep</sup> variables indicates the minimum value of the requirement imposed in the final SR selection. The m<sub>ℓℓ</sub> and m<sub>T2</sub> distributions (right) have all the SR requirements applied. Background processes containing fewer than two prompt leptons are categorized as `Fake/nonprompt'. The category `Others' contains rare backgrounds from triboson, Higgs boson, and the remaining top-quark production processes listed in Table 1. The uncertainty bands plotted include all statistical and systematic uncertainties. The last bin includes overflow. The dashed lines represent benchmark signal samples corresponding to the Higgsino H̃ and slepton ℓ̃ simplified models. Orange arrows in the Data/SM panel indicate values that are beyond the y-axis range.
<b>Kinematics 1</b> Kinematic distributions after the background-only fit showing the data as well as the expected background in the inclusive electroweakino SRℓℓ-m<sub>ℓℓ</sub> [1, 60] (top) and slepton SRℓℓ-m<sub>T2</sub><sup>100</sup> [100, ∞] (bottom) signal regions. The arrow in the E<sub>T</sub><sup>miss</sup>/H<sub>T</sub><sup>lep</sup> variables indicates the minimum value of the requirement imposed in the final SR selection. The m<sub>ℓℓ</sub> and m<sub>T2</sub> distributions (right) have all the SR requirements applied. Background processes containing fewer than two prompt leptons are categorized as `Fake/nonprompt'. The category `Others' contains rare backgrounds from triboson, Higgs boson, and the remaining top-quark production processes listed in Table 1. The uncertainty bands plotted include all statistical and systematic uncertainties. The last bin includes overflow. The dashed lines represent benchmark signal samples corresponding to the Higgsino H̃ and slepton ℓ̃ simplified models. Orange arrows in the Data/SM panel indicate values that are beyond the y-axis range.
<b>Kinematics 2</b> Kinematic distributions after the background-only fit showing the data as well as the expected background in the inclusive electroweakino SRℓℓ-m<sub>ℓℓ</sub> [1, 60] (top) and slepton SRℓℓ-m<sub>T2</sub><sup>100</sup> [100, ∞] (bottom) signal regions. The arrow in the E<sub>T</sub><sup>miss</sup>/H<sub>T</sub><sup>lep</sup> variables indicates the minimum value of the requirement imposed in the final SR selection. The m<sub>ℓℓ</sub> and m<sub>T2</sub> distributions (right) have all the SR requirements applied. Background processes containing fewer than two prompt leptons are categorized as `Fake/nonprompt'. The category `Others' contains rare backgrounds from triboson, Higgs boson, and the remaining top-quark production processes listed in Table 1. The uncertainty bands plotted include all statistical and systematic uncertainties. The last bin includes overflow. The dashed lines represent benchmark signal samples corresponding to the Higgsino H̃ and slepton ℓ̃ simplified models. Orange arrows in the Data/SM panel indicate values that are beyond the y-axis range.
<b>Kinematics 2</b> Kinematic distributions after the background-only fit showing the data as well as the expected background in the inclusive electroweakino SRℓℓ-m<sub>ℓℓ</sub> [1, 60] (top) and slepton SRℓℓ-m<sub>T2</sub><sup>100</sup> [100, ∞] (bottom) signal regions. The arrow in the E<sub>T</sub><sup>miss</sup>/H<sub>T</sub><sup>lep</sup> variables indicates the minimum value of the requirement imposed in the final SR selection. The m<sub>ℓℓ</sub> and m<sub>T2</sub> distributions (right) have all the SR requirements applied. Background processes containing fewer than two prompt leptons are categorized as `Fake/nonprompt'. The category `Others' contains rare backgrounds from triboson, Higgs boson, and the remaining top-quark production processes listed in Table 1. The uncertainty bands plotted include all statistical and systematic uncertainties. The last bin includes overflow. The dashed lines represent benchmark signal samples corresponding to the Higgsino H̃ and slepton ℓ̃ simplified models. Orange arrows in the Data/SM panel indicate values that are beyond the y-axis range.
<b>Kinematics 3</b> Kinematic distributions after the background-only fit showing the data as well as the expected background in the inclusive electroweakino SRℓℓ-m<sub>ℓℓ</sub> [1, 60] (top) and slepton SRℓℓ-m<sub>T2</sub><sup>100</sup> [100, ∞] (bottom) signal regions. The arrow in the E<sub>T</sub><sup>miss</sup>/H<sub>T</sub><sup>lep</sup> variables indicates the minimum value of the requirement imposed in the final SR selection. The m<sub>ℓℓ</sub> and m<sub>T2</sub> distributions (right) have all the SR requirements applied. Background processes containing fewer than two prompt leptons are categorized as `Fake/nonprompt'. The category `Others' contains rare backgrounds from triboson, Higgs boson, and the remaining top-quark production processes listed in Table 1. The uncertainty bands plotted include all statistical and systematic uncertainties. The last bin includes overflow. The dashed lines represent benchmark signal samples corresponding to the Higgsino H̃ and slepton ℓ̃ simplified models. Orange arrows in the Data/SM panel indicate values that are beyond the y-axis range.
<b>Kinematics 3</b> Kinematic distributions after the background-only fit showing the data as well as the expected background in the inclusive electroweakino SRℓℓ-m<sub>ℓℓ</sub> [1, 60] (top) and slepton SRℓℓ-m<sub>T2</sub><sup>100</sup> [100, ∞] (bottom) signal regions. The arrow in the E<sub>T</sub><sup>miss</sup>/H<sub>T</sub><sup>lep</sup> variables indicates the minimum value of the requirement imposed in the final SR selection. The m<sub>ℓℓ</sub> and m<sub>T2</sub> distributions (right) have all the SR requirements applied. Background processes containing fewer than two prompt leptons are categorized as `Fake/nonprompt'. The category `Others' contains rare backgrounds from triboson, Higgs boson, and the remaining top-quark production processes listed in Table 1. The uncertainty bands plotted include all statistical and systematic uncertainties. The last bin includes overflow. The dashed lines represent benchmark signal samples corresponding to the Higgsino H̃ and slepton ℓ̃ simplified models. Orange arrows in the Data/SM panel indicate values that are beyond the y-axis range.
<b>Kinematics 4</b> Kinematic distributions after the background-only fit showing the data as well as the expected background in the inclusive electroweakino SRℓℓ-m<sub>ℓℓ</sub> [1, 60] (top) and slepton SRℓℓ-m<sub>T2</sub><sup>100</sup> [100, ∞] (bottom) signal regions. The arrow in the E<sub>T</sub><sup>miss</sup>/H<sub>T</sub><sup>lep</sup> variables indicates the minimum value of the requirement imposed in the final SR selection. The m<sub>ℓℓ</sub> and m<sub>T2</sub> distributions (right) have all the SR requirements applied. Background processes containing fewer than two prompt leptons are categorized as `Fake/nonprompt'. The category `Others' contains rare backgrounds from triboson, Higgs boson, and the remaining top-quark production processes listed in Table 1. The uncertainty bands plotted include all statistical and systematic uncertainties. The last bin includes overflow. The dashed lines represent benchmark signal samples corresponding to the Higgsino H̃ and slepton ℓ̃ simplified models. Orange arrows in the Data/SM panel indicate values that are beyond the y-axis range.
<b>Kinematics 4</b> Kinematic distributions after the background-only fit showing the data as well as the expected background in the inclusive electroweakino SRℓℓ-m<sub>ℓℓ</sub> [1, 60] (top) and slepton SRℓℓ-m<sub>T2</sub><sup>100</sup> [100, ∞] (bottom) signal regions. The arrow in the E<sub>T</sub><sup>miss</sup>/H<sub>T</sub><sup>lep</sup> variables indicates the minimum value of the requirement imposed in the final SR selection. The m<sub>ℓℓ</sub> and m<sub>T2</sub> distributions (right) have all the SR requirements applied. Background processes containing fewer than two prompt leptons are categorized as `Fake/nonprompt'. The category `Others' contains rare backgrounds from triboson, Higgs boson, and the remaining top-quark production processes listed in Table 1. The uncertainty bands plotted include all statistical and systematic uncertainties. The last bin includes overflow. The dashed lines represent benchmark signal samples corresponding to the Higgsino H̃ and slepton ℓ̃ simplified models. Orange arrows in the Data/SM panel indicate values that are beyond the y-axis range.
<b>Exclusion 1 (exp)</b> Expected 95% CL exclusion sensitivity (blue dashed line) with pm1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and observed limits (red solid line) with pm1σ<sub>theory</sub> (dotted red line) from signal cross-section uncertainties for simplified models of direct Higgsino (top) and wino (bottom) production. A fit of signals to the m<sub>ℓℓ</sub> spectrum is used to derive the limit, which is projected into the Δ m(χ̃<sub>2</sub><sup>0</sup>, χ̃<sub>1</sub><sup>0</sup>) vs. m(χ̃<sub>2</sub><sup>0</sup>) plane. For Higgsino production, the chargino χ̃<sub>1</sub><sup>pm</sup> mass is assumed to be halfway between the two lightest neutralino masses, while m(χ̃<sub>2</sub><sup>0</sup>) = m(χ̃<sub>1</sub><sup>pm</sup>) is assumed for the wino--bino model. The gray regions denote the lower chargino mass limit from LEP [20]. The blue region in the lower plot indicates the limit from the 2ℓ+3ℓ combination of ATLAS Run 1 [41,42].
<b>Exclusion 1 (exp)</b> Expected 95% CL exclusion sensitivity (blue dashed line) with pm1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and observed limits (red solid line) with pm1σ<sub>theory</sub> (dotted red line) from signal cross-section uncertainties for simplified models of direct Higgsino (top) and wino (bottom) production. A fit of signals to the m<sub>ℓℓ</sub> spectrum is used to derive the limit, which is projected into the Δ m(χ̃<sub>2</sub><sup>0</sup>, χ̃<sub>1</sub><sup>0</sup>) vs. m(χ̃<sub>2</sub><sup>0</sup>) plane. For Higgsino production, the chargino χ̃<sub>1</sub><sup>pm</sup> mass is assumed to be halfway between the two lightest neutralino masses, while m(χ̃<sub>2</sub><sup>0</sup>) = m(χ̃<sub>1</sub><sup>pm</sup>) is assumed for the wino--bino model. The gray regions denote the lower chargino mass limit from LEP [20]. The blue region in the lower plot indicates the limit from the 2ℓ+3ℓ combination of ATLAS Run 1 [41,42].
<b>Exclusion 1 (obs)</b> Expected 95% CL exclusion sensitivity (blue dashed line) with pm1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and observed limits (red solid line) with pm1σ<sub>theory</sub> (dotted red line) from signal cross-section uncertainties for simplified models of direct Higgsino (top) and wino (bottom) production. A fit of signals to the m<sub>ℓℓ</sub> spectrum is used to derive the limit, which is projected into the Δ m(χ̃<sub>2</sub><sup>0</sup>, χ̃<sub>1</sub><sup>0</sup>) vs. m(χ̃<sub>2</sub><sup>0</sup>) plane. For Higgsino production, the chargino χ̃<sub>1</sub><sup>pm</sup> mass is assumed to be halfway between the two lightest neutralino masses, while m(χ̃<sub>2</sub><sup>0</sup>) = m(χ̃<sub>1</sub><sup>pm</sup>) is assumed for the wino--bino model. The gray regions denote the lower chargino mass limit from LEP [20]. The blue region in the lower plot indicates the limit from the 2ℓ+3ℓ combination of ATLAS Run 1 [41,42].
<b>Exclusion 1 (obs)</b> Expected 95% CL exclusion sensitivity (blue dashed line) with pm1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and observed limits (red solid line) with pm1σ<sub>theory</sub> (dotted red line) from signal cross-section uncertainties for simplified models of direct Higgsino (top) and wino (bottom) production. A fit of signals to the m<sub>ℓℓ</sub> spectrum is used to derive the limit, which is projected into the Δ m(χ̃<sub>2</sub><sup>0</sup>, χ̃<sub>1</sub><sup>0</sup>) vs. m(χ̃<sub>2</sub><sup>0</sup>) plane. For Higgsino production, the chargino χ̃<sub>1</sub><sup>pm</sup> mass is assumed to be halfway between the two lightest neutralino masses, while m(χ̃<sub>2</sub><sup>0</sup>) = m(χ̃<sub>1</sub><sup>pm</sup>) is assumed for the wino--bino model. The gray regions denote the lower chargino mass limit from LEP [20]. The blue region in the lower plot indicates the limit from the 2ℓ+3ℓ combination of ATLAS Run 1 [41,42].
<b>Exclusion 2 (exp)</b> Expected 95% CL exclusion sensitivity (blue dashed line) with pm1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and observed limits (red solid line) with pm1σ<sub>theory</sub> (dotted red line) from signal cross-section uncertainties for simplified models of direct Higgsino (top) and wino (bottom) production. A fit of signals to the m<sub>ℓℓ</sub> spectrum is used to derive the limit, which is projected into the Δ m(χ̃<sub>2</sub><sup>0</sup>, χ̃<sub>1</sub><sup>0</sup>) vs. m(χ̃<sub>2</sub><sup>0</sup>) plane. For Higgsino production, the chargino χ̃<sub>1</sub><sup>pm</sup> mass is assumed to be halfway between the two lightest neutralino masses, while m(χ̃<sub>2</sub><sup>0</sup>) = m(χ̃<sub>1</sub><sup>pm</sup>) is assumed for the wino--bino model. The gray regions denote the lower chargino mass limit from LEP [20]. The blue region in the lower plot indicates the limit from the 2ℓ+3ℓ combination of ATLAS Run 1 [41,42].
<b>Exclusion 2 (exp)</b> Expected 95% CL exclusion sensitivity (blue dashed line) with pm1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and observed limits (red solid line) with pm1σ<sub>theory</sub> (dotted red line) from signal cross-section uncertainties for simplified models of direct Higgsino (top) and wino (bottom) production. A fit of signals to the m<sub>ℓℓ</sub> spectrum is used to derive the limit, which is projected into the Δ m(χ̃<sub>2</sub><sup>0</sup>, χ̃<sub>1</sub><sup>0</sup>) vs. m(χ̃<sub>2</sub><sup>0</sup>) plane. For Higgsino production, the chargino χ̃<sub>1</sub><sup>pm</sup> mass is assumed to be halfway between the two lightest neutralino masses, while m(χ̃<sub>2</sub><sup>0</sup>) = m(χ̃<sub>1</sub><sup>pm</sup>) is assumed for the wino--bino model. The gray regions denote the lower chargino mass limit from LEP [20]. The blue region in the lower plot indicates the limit from the 2ℓ+3ℓ combination of ATLAS Run 1 [41,42].
<b>Exclusion 2 (obs)</b> Expected 95% CL exclusion sensitivity (blue dashed line) with pm1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and observed limits (red solid line) with pm1σ<sub>theory</sub> (dotted red line) from signal cross-section uncertainties for simplified models of direct Higgsino (top) and wino (bottom) production. A fit of signals to the m<sub>ℓℓ</sub> spectrum is used to derive the limit, which is projected into the Δ m(χ̃<sub>2</sub><sup>0</sup>, χ̃<sub>1</sub><sup>0</sup>) vs. m(χ̃<sub>2</sub><sup>0</sup>) plane. For Higgsino production, the chargino χ̃<sub>1</sub><sup>pm</sup> mass is assumed to be halfway between the two lightest neutralino masses, while m(χ̃<sub>2</sub><sup>0</sup>) = m(χ̃<sub>1</sub><sup>pm</sup>) is assumed for the wino--bino model. The gray regions denote the lower chargino mass limit from LEP [20]. The blue region in the lower plot indicates the limit from the 2ℓ+3ℓ combination of ATLAS Run 1 [41,42].
<b>Exclusion 2 (obs)</b> Expected 95% CL exclusion sensitivity (blue dashed line) with pm1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and observed limits (red solid line) with pm1σ<sub>theory</sub> (dotted red line) from signal cross-section uncertainties for simplified models of direct Higgsino (top) and wino (bottom) production. A fit of signals to the m<sub>ℓℓ</sub> spectrum is used to derive the limit, which is projected into the Δ m(χ̃<sub>2</sub><sup>0</sup>, χ̃<sub>1</sub><sup>0</sup>) vs. m(χ̃<sub>2</sub><sup>0</sup>) plane. For Higgsino production, the chargino χ̃<sub>1</sub><sup>pm</sup> mass is assumed to be halfway between the two lightest neutralino masses, while m(χ̃<sub>2</sub><sup>0</sup>) = m(χ̃<sub>1</sub><sup>pm</sup>) is assumed for the wino--bino model. The gray regions denote the lower chargino mass limit from LEP [20]. The blue region in the lower plot indicates the limit from the 2ℓ+3ℓ combination of ATLAS Run 1 [41,42].
<b>Exclusion 3 (exp)</b> Expected 95% CL exclusion sensitivity (blue dashed line) with ± 1 σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and observed limits (red solid line) with ± 1 σ<sub>theory</sub> (dotted red line) from signal cross-section uncertainties for simplified models of direct slepton production. A fit of slepton signals to the m<sub>T2</sub><sup>100</sup> spectrum is used to derive the limit, which is projected into the Δ m(ℓ̃, χ̃<sub>1</sub><sup>0</sup>) vs. m(ℓ̃) plane. Slepton ℓ̃ refers to the scalar partners of left- and right-handed electrons and muons, which are assumed to be fourfold mass degenerate m(ẽ<sub>L</sub>) = m(ẽ<sub>R</sub>) = m(μ̃<sub>L</sub>) = m(μ̃<sub>R</sub>). The gray region is the ẽ<sub>R</sub> limit from LEP [20,24], while the blue region is the fourfold mass degenerate slepton limit from ATLAS Run 1 [41].
<b>Exclusion 3 (exp)</b> Expected 95% CL exclusion sensitivity (blue dashed line) with ± 1 σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and observed limits (red solid line) with ± 1 σ<sub>theory</sub> (dotted red line) from signal cross-section uncertainties for simplified models of direct slepton production. A fit of slepton signals to the m<sub>T2</sub><sup>100</sup> spectrum is used to derive the limit, which is projected into the Δ m(ℓ̃, χ̃<sub>1</sub><sup>0</sup>) vs. m(ℓ̃) plane. Slepton ℓ̃ refers to the scalar partners of left- and right-handed electrons and muons, which are assumed to be fourfold mass degenerate m(ẽ<sub>L</sub>) = m(ẽ<sub>R</sub>) = m(μ̃<sub>L</sub>) = m(μ̃<sub>R</sub>). The gray region is the ẽ<sub>R</sub> limit from LEP [20,24], while the blue region is the fourfold mass degenerate slepton limit from ATLAS Run 1 [41].
<b>Exclusion 3 (obs)</b> Expected 95% CL exclusion sensitivity (blue dashed line) with ± 1 σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and observed limits (red solid line) with ± 1 σ<sub>theory</sub> (dotted red line) from signal cross-section uncertainties for simplified models of direct slepton production. A fit of slepton signals to the m<sub>T2</sub><sup>100</sup> spectrum is used to derive the limit, which is projected into the Δ m(ℓ̃, χ̃<sub>1</sub><sup>0</sup>) vs. m(ℓ̃) plane. Slepton ℓ̃ refers to the scalar partners of left- and right-handed electrons and muons, which are assumed to be fourfold mass degenerate m(ẽ<sub>L</sub>) = m(ẽ<sub>R</sub>) = m(μ̃<sub>L</sub>) = m(μ̃<sub>R</sub>). The gray region is the ẽ<sub>R</sub> limit from LEP [20,24], while the blue region is the fourfold mass degenerate slepton limit from ATLAS Run 1 [41].
<b>Exclusion 3 (obs)</b> Expected 95% CL exclusion sensitivity (blue dashed line) with ± 1 σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and observed limits (red solid line) with ± 1 σ<sub>theory</sub> (dotted red line) from signal cross-section uncertainties for simplified models of direct slepton production. A fit of slepton signals to the m<sub>T2</sub><sup>100</sup> spectrum is used to derive the limit, which is projected into the Δ m(ℓ̃, χ̃<sub>1</sub><sup>0</sup>) vs. m(ℓ̃) plane. Slepton ℓ̃ refers to the scalar partners of left- and right-handed electrons and muons, which are assumed to be fourfold mass degenerate m(ẽ<sub>L</sub>) = m(ẽ<sub>R</sub>) = m(μ̃<sub>L</sub>) = m(μ̃<sub>R</sub>). The gray region is the ẽ<sub>R</sub> limit from LEP [20,24], while the blue region is the fourfold mass degenerate slepton limit from ATLAS Run 1 [41].
<b>Upper Limits 1</b> The first two columns present observed (N<sub>obs</sub>) and expected (N<sub>exp</sub>) event yields in the inclusive signal regions. The latter are obtained by the background-only fit of the control regions, and the errors include both statistical and systematic uncertainties. The next two columns show the observed 95% CL upper limits on the visible cross-section (⟨εσ⟩<sub>obs</sub><sup>95</sup>) and on the number of signal events (S<sub>obs</sub><sup>95</sup>). The fifth column (S<sub>exp</sub><sup>95</sup>) shows what the 95% CL upper limit on the number of signal events would be, given an observed number of events equal to the expected number (and +- 1 σ deviations from the expectation) of background events. The last column indicates the discovery p-value (p(s = 0)), which is capped at 0.5.
<b>Upper Limits 1</b> The first two columns present observed (N<sub>obs</sub>) and expected (N<sub>exp</sub>) event yields in the inclusive signal regions. The latter are obtained by the background-only fit of the control regions, and the errors include both statistical and systematic uncertainties. The next two columns show the observed 95% CL upper limits on the visible cross-section (⟨εσ⟩<sub>obs</sub><sup>95</sup>) and on the number of signal events (S<sub>obs</sub><sup>95</sup>). The fifth column (S<sub>exp</sub><sup>95</sup>) shows what the 95% CL upper limit on the number of signal events would be, given an observed number of events equal to the expected number (and +- 1 σ deviations from the expectation) of background events. The last column indicates the discovery p-value (p(s = 0)), which is capped at 0.5.
<b>Cutflow 1</b> Observed event yields and exclusion fit results with the signal strength parameter set to zero for the exclusive electroweakino and slepton signal regions. Background processes containing fewer than two prompt leptons are categorized as `Fake/nonprompt'. The category `Others' contains rare backgrounds from triboson, Higgs boson, and the remaining top-quark production processes listed in Table 1. Uncertainties in the fitted background estimates combine statistical and systematic uncertainties.
<b>Cutflow 1</b> Observed event yields and exclusion fit results with the signal strength parameter set to zero for the exclusive electroweakino and slepton signal regions. Background processes containing fewer than two prompt leptons are categorized as `Fake/nonprompt'. The category `Others' contains rare backgrounds from triboson, Higgs boson, and the remaining top-quark production processes listed in Table 1. Uncertainties in the fitted background estimates combine statistical and systematic uncertainties.
<b>Acceptances 1</b> Truth acceptances for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>±</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>4</sup>.
<b>Acceptances 1</b> Truth acceptances for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>±</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>4</sup>.
<b>Acceptances 2</b> Truth acceptances for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>±</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>4</sup>.
<b>Acceptances 2</b> Truth acceptances for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>±</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>4</sup>.
<b>Acceptances 3</b> Truth acceptances for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>±</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>4</sup>.
<b>Acceptances 3</b> Truth acceptances for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>±</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>4</sup>.
<b>Acceptances 4</b> Truth acceptances for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>±</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>4</sup>.
<b>Acceptances 4</b> Truth acceptances for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>±</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>4</sup>.
<b>Acceptances 5</b> Truth acceptances for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>±</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>4</sup>.
<b>Acceptances 5</b> Truth acceptances for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>±</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>4</sup>.
<b>Acceptances 6</b> Truth acceptances for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>±</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>4</sup>.
<b>Acceptances 6</b> Truth acceptances for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>±</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>4</sup>.
<b>Acceptances 7</b> Truth acceptances for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>±</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>4</sup>.
<b>Acceptances 7</b> Truth acceptances for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>±</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>4</sup>.
<b>Acceptances 8</b> Truth acceptances for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>+</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>4</sup>.
<b>Acceptances 8</b> Truth acceptances for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>+</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>4</sup>.
<b>Acceptances 9</b> Truth acceptances for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>+</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>4</sup>.
<b>Acceptances 9</b> Truth acceptances for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>+</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>4</sup>.
<b>Acceptances 10</b> Truth acceptances for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>+</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>4</sup>.
<b>Acceptances 10</b> Truth acceptances for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>+</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>4</sup>.
<b>Acceptances 11</b> Truth acceptances for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>+</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>4</sup>.
<b>Acceptances 11</b> Truth acceptances for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>+</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>4</sup>.
<b>Acceptances 12</b> Truth acceptances for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>+</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>4</sup>.
<b>Acceptances 12</b> Truth acceptances for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>+</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>4</sup>.
<b>Acceptances 13</b> Truth acceptances for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>+</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>4</sup>.
<b>Acceptances 13</b> Truth acceptances for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>+</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>4</sup>.
<b>Acceptances 14</b> Truth acceptances for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>+</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>4</sup>.
<b>Acceptances 14</b> Truth acceptances for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>+</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>4</sup>.
<b>Acceptances 15</b> Truth acceptances for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>0</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>4</sup>.
<b>Acceptances 15</b> Truth acceptances for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>0</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>4</sup>.
<b>Acceptances 16</b> Truth acceptances for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>0</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>4</sup>.
<b>Acceptances 16</b> Truth acceptances for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>0</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>4</sup>.
<b>Acceptances 17</b> Truth acceptances for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>0</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>4</sup>.
<b>Acceptances 17</b> Truth acceptances for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>0</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>4</sup>.
<b>Acceptances 18</b> Truth acceptances for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>0</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>4</sup>.
<b>Acceptances 18</b> Truth acceptances for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>0</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>4</sup>.
<b>Acceptances 19</b> Truth acceptances for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>0</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>4</sup>.
<b>Acceptances 19</b> Truth acceptances for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>0</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>4</sup>.
<b>Acceptances 20</b> Truth acceptances for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>0</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>4</sup>.
<b>Acceptances 20</b> Truth acceptances for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>0</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>4</sup>.
<b>Acceptances 21</b> Truth acceptances for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>0</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>4</sup>.
<b>Acceptances 21</b> Truth acceptances for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>0</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>4</sup>.
<b>Acceptances 22</b> Truth acceptances for the Higgsino χ̃<sub>1</sub><sup>+</sup>χ̃<sub>1</sub><sup>-</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>4</sup>.
<b>Acceptances 22</b> Truth acceptances for the Higgsino χ̃<sub>1</sub><sup>+</sup>χ̃<sub>1</sub><sup>-</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>4</sup>.
<b>Acceptances 23</b> Truth acceptances for the Higgsino χ̃<sub>1</sub><sup>+</sup>χ̃<sub>1</sub><sup>-</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>4</sup>.
<b>Acceptances 23</b> Truth acceptances for the Higgsino χ̃<sub>1</sub><sup>+</sup>χ̃<sub>1</sub><sup>-</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>4</sup>.
<b>Acceptances 24</b> Truth acceptances for the Higgsino χ̃<sub>1</sub><sup>+</sup>χ̃<sub>1</sub><sup>-</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>4</sup>.
<b>Acceptances 24</b> Truth acceptances for the Higgsino χ̃<sub>1</sub><sup>+</sup>χ̃<sub>1</sub><sup>-</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>4</sup>.
<b>Acceptances 25</b> Truth acceptances for the Higgsino χ̃<sub>1</sub><sup>+</sup>χ̃<sub>1</sub><sup>-</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>4</sup>.
<b>Acceptances 25</b> Truth acceptances for the Higgsino χ̃<sub>1</sub><sup>+</sup>χ̃<sub>1</sub><sup>-</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>4</sup>.
<b>Acceptances 26</b> Truth acceptances for the Higgsino χ̃<sub>1</sub><sup>+</sup>χ̃<sub>1</sub><sup>-</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>4</sup>.
<b>Acceptances 26</b> Truth acceptances for the Higgsino χ̃<sub>1</sub><sup>+</sup>χ̃<sub>1</sub><sup>-</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>4</sup>.
<b>Acceptances 27</b> Truth acceptances for the Higgsino χ̃<sub>1</sub><sup>+</sup>χ̃<sub>1</sub><sup>-</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>4</sup>.
<b>Acceptances 27</b> Truth acceptances for the Higgsino χ̃<sub>1</sub><sup>+</sup>χ̃<sub>1</sub><sup>-</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>4</sup>.
<b>Acceptances 28</b> Truth acceptances for the Higgsino χ̃<sub>1</sub><sup>+</sup>χ̃<sub>1</sub><sup>-</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>4</sup>.
<b>Acceptances 28</b> Truth acceptances for the Higgsino χ̃<sub>1</sub><sup>+</sup>χ̃<sub>1</sub><sup>-</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>4</sup>.
<b>Acceptances 29</b> Truth acceptances for the ℓ̃ℓ̃ production in the inclusive SRℓℓ-m<sub>T2</sub><sup>100</sup> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>3</sup>.
<b>Acceptances 29</b> Truth acceptances for the ℓ̃ℓ̃ production in the inclusive SRℓℓ-m<sub>T2</sub><sup>100</sup> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>3</sup>.
<b>Acceptances 30</b> Truth acceptances for the ℓ̃ℓ̃ production in the inclusive SRℓℓ-m<sub>T2</sub><sup>100</sup> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>3</sup>.
<b>Acceptances 30</b> Truth acceptances for the ℓ̃ℓ̃ production in the inclusive SRℓℓ-m<sub>T2</sub><sup>100</sup> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>3</sup>.
<b>Acceptances 31</b> Truth acceptances for the ℓ̃ℓ̃ production in the inclusive SRℓℓ-m<sub>T2</sub><sup>100</sup> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>3</sup>.
<b>Acceptances 31</b> Truth acceptances for the ℓ̃ℓ̃ production in the inclusive SRℓℓ-m<sub>T2</sub><sup>100</sup> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>3</sup>.
<b>Acceptances 32</b> Truth acceptances for the ℓ̃ℓ̃ production in the inclusive SRℓℓ-m<sub>T2</sub><sup>100</sup> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>3</sup>.
<b>Acceptances 32</b> Truth acceptances for the ℓ̃ℓ̃ production in the inclusive SRℓℓ-m<sub>T2</sub><sup>100</sup> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>3</sup>.
<b>Acceptances 33</b> Truth acceptances for the ℓ̃ℓ̃ production in the inclusive SRℓℓ-m<sub>T2</sub><sup>100</sup> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>3</sup>.
<b>Acceptances 33</b> Truth acceptances for the ℓ̃ℓ̃ production in the inclusive SRℓℓ-m<sub>T2</sub><sup>100</sup> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>3</sup>.
<b>Acceptances 34</b> Truth acceptances for the ℓ̃ℓ̃ production in the inclusive SRℓℓ-m<sub>T2</sub><sup>100</sup> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>3</sup>.
<b>Acceptances 34</b> Truth acceptances for the ℓ̃ℓ̃ production in the inclusive SRℓℓ-m<sub>T2</sub><sup>100</sup> regions. Numbers overlaid on the mass planes are the acceptance × 10<sup>3</sup>.
<b>Efficiencies 1</b> Efficiencies for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>+</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 1</b> Efficiencies for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>+</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 2</b> Efficiencies for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>+</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 2</b> Efficiencies for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>+</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 3</b> Efficiencies for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>+</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 3</b> Efficiencies for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>+</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 4</b> Efficiencies for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>+</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 4</b> Efficiencies for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>+</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 5</b> Efficiencies for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>+</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 5</b> Efficiencies for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>+</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 6</b> Efficiencies for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>+</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 6</b> Efficiencies for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>+</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 7</b> Efficiencies for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>+</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 7</b> Efficiencies for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>+</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 8</b> Efficiencies for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>-</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 8</b> Efficiencies for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>-</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 9</b> Efficiencies for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>-</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 9</b> Efficiencies for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>-</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 10</b> Efficiencies for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>-</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 10</b> Efficiencies for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>-</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 11</b> Efficiencies for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>-</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 11</b> Efficiencies for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>-</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 12</b> Efficiencies for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>-</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 12</b> Efficiencies for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>-</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 13</b> Efficiencies for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>-</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 13</b> Efficiencies for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>-</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 14</b> Efficiencies for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>-</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 14</b> Efficiencies for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>-</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 15</b> Efficiencies for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>0</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 15</b> Efficiencies for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>0</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 16</b> Efficiencies for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>0</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 16</b> Efficiencies for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>0</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 17</b> Efficiencies for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>0</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 17</b> Efficiencies for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>0</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 18</b> Efficiencies for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>0</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 18</b> Efficiencies for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>0</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 19</b> Efficiencies for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>0</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 19</b> Efficiencies for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>0</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 20</b> Efficiencies for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>0</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 20</b> Efficiencies for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>0</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 21</b> Efficiencies for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>0</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 21</b> Efficiencies for the Higgsino χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>0</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 22</b> Efficiencies for the Higgsino χ̃<sub>1</sub><sup>+</sup>χ̃<sub>1</sub><sup>-</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 22</b> Efficiencies for the Higgsino χ̃<sub>1</sub><sup>+</sup>χ̃<sub>1</sub><sup>-</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 23</b> Efficiencies for the Higgsino χ̃<sub>1</sub><sup>+</sup>χ̃<sub>1</sub><sup>-</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 24</b> Efficiencies for the Higgsino χ̃<sub>1</sub><sup>+</sup>χ̃<sub>1</sub><sup>-</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 24</b> Efficiencies for the Higgsino χ̃<sub>1</sub><sup>+</sup>χ̃<sub>1</sub><sup>-</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 25</b> Efficiencies for the Higgsino χ̃<sub>1</sub><sup>+</sup>χ̃<sub>1</sub><sup>-</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 25</b> Efficiencies for the Higgsino χ̃<sub>1</sub><sup>+</sup>χ̃<sub>1</sub><sup>-</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 26</b> Efficiencies for the Higgsino χ̃<sub>1</sub><sup>+</sup>χ̃<sub>1</sub><sup>-</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 26</b> Efficiencies for the Higgsino χ̃<sub>1</sub><sup>+</sup>χ̃<sub>1</sub><sup>-</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 27</b> Efficiencies for the Higgsino χ̃<sub>1</sub><sup>+</sup>χ̃<sub>1</sub><sup>-</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 27</b> Efficiencies for the Higgsino χ̃<sub>1</sub><sup>+</sup>χ̃<sub>1</sub><sup>-</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 28</b> Efficiencies for the Higgsino χ̃<sub>1</sub><sup>+</sup>χ̃<sub>1</sub><sup>-</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 28</b> Efficiencies for the Higgsino χ̃<sub>1</sub><sup>+</sup>χ̃<sub>1</sub><sup>-</sup> production process in the inclusive SRℓℓ-m<sub>ℓℓ</sub> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 29</b> Efficiencies for the ℓ̃ℓ̃ production in the inclusive SRℓℓ-m<sub>T2</sub><sup>100</sup> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 29</b> Efficiencies for the ℓ̃ℓ̃ production in the inclusive SRℓℓ-m<sub>T2</sub><sup>100</sup> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 30</b> Efficiencies for the ℓ̃ℓ̃ production in the inclusive SRℓℓ-m<sub>T2</sub><sup>100</sup> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 30</b> Efficiencies for the ℓ̃ℓ̃ production in the inclusive SRℓℓ-m<sub>T2</sub><sup>100</sup> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 31</b> Efficiencies for the ℓ̃ℓ̃ production in the inclusive SRℓℓ-m<sub>T2</sub><sup>100</sup> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 31</b> Efficiencies for the ℓ̃ℓ̃ production in the inclusive SRℓℓ-m<sub>T2</sub><sup>100</sup> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 32</b> Efficiencies for the ℓ̃ℓ̃ production in the inclusive SRℓℓ-m<sub>T2</sub><sup>100</sup> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 32</b> Efficiencies for the ℓ̃ℓ̃ production in the inclusive SRℓℓ-m<sub>T2</sub><sup>100</sup> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 33</b> Efficiencies for the ℓ̃ℓ̃ production in the inclusive SRℓℓ-m<sub>T2</sub><sup>100</sup> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 33</b> Efficiencies for the ℓ̃ℓ̃ production in the inclusive SRℓℓ-m<sub>T2</sub><sup>100</sup> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 34</b> Efficiencies for the ℓ̃ℓ̃ production in the inclusive SRℓℓ-m<sub>T2</sub><sup>100</sup> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Efficiencies 34</b> Efficiencies for the ℓ̃ℓ̃ production in the inclusive SRℓℓ-m<sub>T2</sub><sup>100</sup> regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of Δ m or m<sub>T2</sub> for the inclusive signal region under study.
<b>Cross-Sections 1</b> Cross-sections of the Higgsino signal grid for each production process denoted in the caption.
<b>Cross-Sections 2</b> Cross-sections of the Higgsino signal grid for each production process denoted in the caption.
<b>Cross-Sections 3</b> Cross-sections of the Higgsino signal grid for each production process denoted in the caption.
<b>Cross-Sections 4</b> Cross-sections of the Higgsino signal grid for each production process denoted in the caption.
<b>Cross-Sections 5</b> Cross-sections of the wino--bino signal grid for each production process in the caption.
<b>Cross-Sections 6</b> Cross-sections of the wino--bino signal grid for each production process in the caption.
<b>Cross-Sections 7</b> Total cross-sections of the slepton simplified model signal grid. Slepton refers to a the scalar partners of the left- and right-handed electrons and muons, which are assumed to be mass degenerate m(ẽ<sub>L</sub>) = m(ẽ<sub>R</sub>) = m(μ̃<sub>L</sub>) = m(μ̃<sub>R</sub>).
<b>Kinematics 5</b> Distributions after the background-only fit of kinematic variables used to define selections common to all signal regions, i.e. not including requirements specific to the electroweakino or slepton SR definitions. Blue arrows in the upper panel denote the final requirement used to define the common SR, otherwise all selections are applied. The category `Others' contains rare backgrounds from triboson, Higgs boson, and the remaining top-quark production processes listed in Table 1. The first (last) bin includes underflow (overflow). Benchmark Higgsino H̃ and slepton ℓ̃ signals are overlaid as dashed lines. Orange arrows in the Data/SM panel indicate values that are beyond the y-axis range.
<b>Kinematics 6</b> Distributions after the background-only fit of kinematic variables used to define selections common to all signal regions, i.e. not including requirements specific to the electroweakino or slepton SR definitions. Blue arrows in the upper panel denote the final requirement used to define the common SR, otherwise all selections are applied. The category `Others' contains rare backgrounds from triboson, Higgs boson, and the remaining top-quark production processes listed in Table 1. The first (last) bin includes underflow (overflow). Benchmark Higgsino H̃ and slepton ℓ̃ signals are overlaid as dashed lines. Orange arrows in the Data/SM panel indicate values that are beyond the y-axis range.
<b>Kinematics 7</b> Distributions after the background-only fit of kinematic variables used to define selections common to all signal regions, i.e. not including requirements specific to the electroweakino or slepton SR definitions. Blue arrows in the upper panel denote the final requirement used to define the common SR, otherwise all selections are applied. The category `Others' contains rare backgrounds from triboson, Higgs boson, and the remaining top-quark production processes listed in Table 1. The first (last) bin includes underflow (overflow). Benchmark Higgsino H̃ and slepton ℓ̃ signals are overlaid as dashed lines. Orange arrows in the Data/SM panel indicate values that are beyond the y-axis range.
<b>Kinematics 8</b> Distributions after the background-only fit of kinematic variables used to define selections common to all signal regions, i.e. not including requirements specific to the electroweakino or slepton SR definitions. Blue arrows in the upper panel denote the final requirement used to define the common SR, otherwise all selections are applied. The category `Others' contains rare backgrounds from triboson, Higgs boson, and the remaining top-quark production processes listed in Table 1. The first (last) bin includes underflow (overflow). Benchmark Higgsino H̃ and slepton ℓ̃ signals are overlaid as dashed lines. Orange arrows in the Data/SM panel indicate values that are beyond the y-axis range.
<b>Kinematics 9</b> Distributions after the background-only fit of kinematic variables used to define selections common to all signal regions, i.e. not including requirements specific to the electroweakino or slepton SR definitions. Blue arrows in the upper panel denote the final requirement used to define the common SR, otherwise all selections are applied. The category `Others' contains rare backgrounds from triboson, Higgs boson, and the remaining top-quark production processes listed in Table 1. The first (last) bin includes underflow (overflow). Benchmark Higgsino H̃ and slepton ℓ̃ signals are overlaid as dashed lines. Orange arrows in the Data/SM panel indicate values that are beyond the y-axis range.
<b>Kinematics 10</b> Distributions after the background-only fit of kinematic variables used to define selections common to all signal regions, i.e. not including requirements specific to the electroweakino or slepton SR definitions. Blue arrows in the upper panel denote the final requirement used to define the common SR, otherwise all selections are applied. The category `Others' contains rare backgrounds from triboson, Higgs boson, and the remaining top-quark production processes listed in Table 1. The first (last) bin includes underflow (overflow). Benchmark Higgsino H̃ and slepton ℓ̃ signals are overlaid as dashed lines. Orange arrows in the Data/SM panel indicate values that are beyond the y-axis range.
<b>Kinematics 11</b> Distributions after the background-only fit of kinematic variables used to define selections common to all signal regions, i.e. not including requirements specific to the electroweakino or slepton SR definitions. Blue arrows in the upper panel denote the final requirement used to define the common SR, otherwise all selections are applied. The category `Others' contains rare backgrounds from triboson, Higgs boson, and the remaining top-quark production processes listed in Table 1. The first (last) bin includes underflow (overflow). Benchmark Higgsino H̃ and slepton ℓ̃ signals are overlaid as dashed lines. Orange arrows in the Data/SM panel indicate values that are beyond the y-axis range.
<b>Kinematics 12</b> Distributions after the background-only fit of kinematic variables used to define selections common to all signal regions, i.e. not including requirements specific to the electroweakino or slepton SR definitions. Blue arrows in the upper panel denote the final requirement used to define the common SR, otherwise all selections are applied. The category `Others' contains rare backgrounds from triboson, Higgs boson, and the remaining top-quark production processes listed in Table 1. The first (last) bin includes underflow (overflow). Benchmark Higgsino H̃ and slepton ℓ̃ signals are overlaid as dashed lines. Orange arrows in the Data/SM panel indicate values that are beyond the y-axis range.
<b>Kinematics 13</b> Distributions after the background-only fit of kinematic variables used to define selections common to all signal regions, i.e. not including requirements specific to the electroweakino or slepton SR definitions. Blue arrows in the upper panel denote the final requirement used to define the common SR, otherwise all selections are applied. The category `Others' contains rare backgrounds from triboson, Higgs boson, and the remaining top-quark production processes listed in Table 1. The first (last) bin includes underflow (overflow). Benchmark Higgsino H̃ and slepton ℓ̃ signals are overlaid as dashed lines. Orange arrows in the Data/SM panel indicate values that are beyond the y-axis range.
<b>Kinematics 14</b> Distributions after the background-only fit of kinematic variables used to define selections common to all signal regions, i.e. not including requirements specific to the electroweakino or slepton SR definitions. Blue arrows in the upper panel denote the final requirement used to define the common SR, otherwise all selections are applied. The category `Others' contains rare backgrounds from triboson, Higgs boson, and the remaining top-quark production processes listed in Table 1. The first (last) bin includes underflow (overflow). Benchmark Higgsino H̃ and slepton ℓ̃ signals are overlaid as dashed lines. Orange arrows in the Data/SM panel indicate values that are beyond the y-axis range.
<b>Kinematics 15</b> Distributions after the background-only fit of kinematic variables used to define selections common to all signal regions, i.e. not including requirements specific to the electroweakino or slepton SR definitions. Blue arrows in the upper panel denote the final requirement used to define the common SR, otherwise all selections are applied. The category `Others' contains rare backgrounds from triboson, Higgs boson, and the remaining top-quark production processes listed in Table 1. The first (last) bin includes underflow (overflow). Benchmark Higgsino H̃ and slepton ℓ̃ signals are overlaid as dashed lines. Orange arrows in the Data/SM panel indicate values that are beyond the y-axis range.
<b>Upper Limits 2</b> Numbers show 95% CL model-dependent upper limits on the inclusive Higgsino signal cross-sections.
<b>Upper Limits 3</b> Numbers show 95% CL model-dependent upper limits on the inclusive Higgsino signal cross-sections.
<b>Upper Limits 4</b> Numbers show 95% CL model-dependent upper limits on the inclusive signal cross-sections of the wino--bino model.
<b>Upper Limits 5</b> Numbers show 95% CL model-dependent upper limits on the inclusive signal cross-sections of the wino--bino model.
<b>Upper Limits 6</b> Numbers show the 95% CL model-dependent upper limits on the slepton signal cross-sections, assuming a fourfold mass degeneracy m(ẽ<sub>L,R</sub>) = m(μ̃<sub>L,R</sub>).
<b>Upper Limits 7</b> Numbers show the 95% CL model-dependent upper limits on the slepton signal cross-sections, assuming a fourfold mass degeneracy m(ẽ<sub>L,R</sub>) = m(μ̃<sub>L,R</sub>).
<b>Upper Limits 8</b> Expected and observed 95% CL cross-section upper limits as a function of the universal gaugino mass m<sub>1/2</sub> for the NUHM2 model. The gray numbers indicate the values of the observed limit. The green and yellow bands around the expected limit indicate the ± 1σ and ± 2σ uncertainties, respectively. The expected signal production cross-sections as well as the associated uncertainty are indicated with the blue solid and dashed lines. The lower x-axis indicates the difference between the χ̃<sub>2</sub><sup>0</sup> and χ̃<sub>1</sub><sup>0</sup> masses for different values of m<sub>1/2</sub>. A fit of signals to the m<sub>ℓℓ</sub> spectrum is used to derive this limit.
<b>Upper Limits 9</b> Expected and observed 95% CL cross-section upper limits as a function of the universal gaugino mass m<sub>1/2</sub> for the NUHM2 model. The gray numbers indicate the values of the observed limit. The green and yellow bands around the expected limit indicate the ± 1σ and ± 2σ uncertainties, respectively. The expected signal production cross-sections as well as the associated uncertainty are indicated with the blue solid and dashed lines. The lower x-axis indicates the difference between the χ̃<sub>2</sub><sup>0</sup> and χ̃<sub>1</sub><sup>0</sup> masses for different values of m<sub>1/2</sub>. A fit of signals to the m<sub>ℓℓ</sub> spectrum is used to derive this limit.
<b>Upper Limits 10</b> Expected and observed 95% CL cross-section upper limits as a function of the universal gaugino mass m<sub>1/2</sub> for the NUHM2 model. The gray numbers indicate the values of the observed limit. The green and yellow bands around the expected limit indicate the ± 1σ and ± 2σ uncertainties, respectively. The expected signal production cross-sections as well as the associated uncertainty are indicated with the blue solid and dashed lines. The lower x-axis indicates the difference between the χ̃<sub>2</sub><sup>0</sup> and χ̃<sub>1</sub><sup>0</sup> masses for different values of m<sub>1/2</sub>. A fit of signals to the m<sub>ℓℓ</sub> spectrum is used to derive this limit.
<b>Cutflow 2</b> Observed event yields and exclusion fit results with the signal strength parameter set to zero for the exclusive electroweakino and slepton signal regions. Background processes containing fewer than two prompt leptons are categorized as `Fake/nonprompt'. The category `Others' contains rare backgrounds from triboson, Higgs boson, and the remaining top-quark production processes listed in Table 1. Uncertainties in the fitted background estimates combine statistical and systematic uncertainties.
<b>Cutflow 3</b> Observed event yields and background-only fit results for the inclusive electroweakino and slepton signal regions. Background processes containing fewer than two prompt leptons are categorized as `Fake/nonprompt'. The category `Others' contains rare backgrounds from triboson, Higgs boson, and the remaining top-quark production processes listed in Table 1. Uncertainties in the fitted background estimates combine statistical and systematic uncertainties.
<b>Exclusion 4</b> Nominal observed and expected CLs values for Higgsino signals.
<b>Exclusion 5</b> Nominal observed and expected CLs values for wino--bino signals.
<b>Exclusion 6</b> Nominal observed and expected CLs values for slepton signals.
<b>Upper Limits 11</b> Upper limits on observed (expected) Higgsino simplified model signal cross section σ<sub>obs (exp)</sub><sup>95</sup> and signal strength σ<sub>obs (exp)</sub><sup>95</sup> / σ<sub>theory</sub>.
<b>Upper Limits 12</b> Upper limits on observed (expected) wino--bino simplified model signal cross section σ<sub>obs (exp)</sub><sup>95</sup> and signal strength σ<sub>obs (exp)</sub><sup>95</sup> / σ<sub>theory</sub>.
<b>Upper Limits 13</b> Upper limits on observed (expected) slepton simplified model signal cross section σ<sub>obs (exp)</sub><sup>95</sup> and signal strength σ<sub>obs (exp)</sub><sup>95</sup> / σ<sub>theory</sub>.
<b>Cutflow 4</b> Event counts for Higgsino H and slepton ℓ signals after sequential selections for the inclusive SRℓℓ-m<sub>ℓℓ</sub> and SRℓℓ-m<sub>T2</sub><sup>100</sup> regions. Weighted events are normalised to mathcalL = 36.1 fb<sup>-1</sup> and the inclusive cross section σ, while raw MC events are also shown. The generator filter with efficiency ε<sub>filt</sub> applied to the Higgsino signal requires truth E<sub>T</sub><sup>miss</sup> > 50 GeV and at least 2 leptons with p<sub>T</sub> > 3 GeV, while only the E<sub>T</sub><sup>miss</sup> > 50 GeV requirement is applied to the slepton signal. The mathcalB refers to the branching ratio Z<sup>(*)</sup> → ℓ<sup>+</sup>ℓ<sup>-</sup> in the Higgsino processes. ``Lepton truth matching" requires that the selected leptons are consistent with being decay products of the SUSY process. ``Lepton author 16 veto" removes a class of electron candidates reconstructed with algorithms designed to identify photon conversions.
<b>Cutflow 5</b> Event counts for the χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>+</sup> process of the Higgsino m(χ̃<sub>2</sub><sup>0</sup>, χ̃<sub>1</sub><sup>0</sup>) = (110, 100) GeV signal and sequentially with each addition requirement for selections common to all signal regions (SRs), followed by those optimised for Higgsinos and sleptons. ``Lepton truth matching" requires that the selected leptons are consistent with being decay products of the SUSY process. ``Lepton author 16 veto" removes a class of electron candidates reconstructed with algorithms designed to identify photon conversions. Weighted events are normalised to 36.1 fb<sup>-1</sup> and the raw Monte Carlo events are also displayed.
<b>Cutflow 6</b> Event counts for the χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>-</sup> process of the Higgsino m(χ̃<sub>2</sub><sup>0</sup>, χ̃<sub>1</sub><sup>0</sup>) = (110, 100) GeV signal and sequentially with each addition requirement for selections common to all signal regions (SRs), followed by those optimised for Higgsinos and sleptons. ``Lepton truth matching" requires that the selected leptons are consistent with being decay products of the SUSY process. ``Lepton author 16 veto" removes a class of electron candidates reconstructed with algorithms designed to identify photon conversions. Weighted events are normalised to 36.1 fb<sup>-1</sup> and the raw Monte Carlo events are also displayed.
<b>Cutflow 7</b> Event counts for the χ̃<sub>2</sub><sup>0</sup>χ̃<sub>1</sub><sup>0</sup> process of the Higgsino m(χ̃<sub>2</sub><sup>0</sup>, χ̃<sub>1</sub><sup>0</sup>) = (110, 100) GeV signal and sequentially with each addition requirement followed by those optimised for Higgsinos and sleptons. Weighted events are normalised to 36.1 fb<sup>-1</sup> and the raw Monte Carlo events are also displayed.
<b>Cutflow 8</b> Event counts for the χ̃<sub>1</sub><sup>+</sup>χ̃<sub>1</sub><sup>-</sup> process of the Higgsino m(χ̃<sub>2</sub><sup>0</sup>, χ̃<sub>1</sub><sup>0</sup>) = (110, 100) GeV signal and sequentially with each addition requirement for selections common to all signal regions (SRs). ``Lepton truth matching" requires that the selected leptons are consistent with being decay products of the SUSY process. ``Lepton author 16 veto" removes a class of electron candidates reconstructed with algorithms designed to identify photon conversions. Weighted events are normalised to 36.1 fb<sup>-1</sup> and the raw Monte Carlo events are also displayed.
A search for new phenomena in final states characterized by high jet multiplicity, an isolated lepton (electron or muon) and either zero or at least three $b$-tagged jets is presented. The search uses 36.1 fb$^{-1}$ of $\sqrt{s}$ = 13 TeV proton-proton collision data collected by the ATLAS experiment at the Large Hadron Collider in 2015 and 2016. The dominant sources of background are estimated using parameterized extrapolations, based on observables at medium jet multiplicity, to predict the $b$-tagged jet multiplicity distribution at the higher jet multiplicities used in the search. No significant excess over the Standard Model expectation is observed and 95% confidence-level limits are extracted constraining four simplified models of $R$-parity-violating supersymmetry that feature either gluino or top-squark pair production. The exclusion limits reach as high as 2.1 TeV in gluino mass and 1.2 TeV in top-squark mass in the models considered. In addition, an upper limit is set on the cross-section for Standard Model $t\bar{t}t\bar{t}$ production of 60 fb (6.5 $\times$ the Standard Model prediction) at 95% confidence level. Finally, model-independent limits are set on the contribution from new phenomena to the signal-region yields.
The expected background and observed data with five jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with five jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with five jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with six jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with six jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with six jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with seven jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with seven jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with seven jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with eight jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with eight jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with eight jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with nine jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with nine jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with nine jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with ten jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with ten jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with ten jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with eleven jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with eleven jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with eleven jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with twelve-or-more jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with twelve-or-more jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with twelve-or-more jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with five jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with five jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with five jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with six jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with six jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with six jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with seven jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with seven jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with seven jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with eight jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with eight jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with eight jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with nine jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with nine jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with nine jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with ten-or-more jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with ten-or-more jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with ten-or-more jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with five jets in the different b-tag multiplicity bins for the 80 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with five jets in the different b-tag multiplicity bins for the 80 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with five jets in the different b-tag multiplicity bins for the 80 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with six jets in the different b-tag multiplicity bins for the 80 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with six jets in the different b-tag multiplicity bins for the 80 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with six jets in the different b-tag multiplicity bins for the 80 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with seven jets in the different b-tag multiplicity bins for the 80 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with seven jets in the different b-tag multiplicity bins for the 80 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with seven jets in the different b-tag multiplicity bins for the 80 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with eight jets in the different b-tag multiplicity bins for the 80 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with eight jets in the different b-tag multiplicity bins for the 80 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with eight jets in the different b-tag multiplicity bins for the 80 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with nine jets in the different b-tag multiplicity bins for the 80 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with nine jets in the different b-tag multiplicity bins for the 80 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with nine jets in the different b-tag multiplicity bins for the 80 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with ten-or-more jets in the different b-tag multiplicity bins for the 80 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with ten-or-more jets in the different b-tag multiplicity bins for the 80 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
Observed exclusion contours on the gluino and neutralino masses in a model where the gluino decays via a virtual top squark to two top quarks and the lightest neutralino, with the neutralino decaying to three light quarks (neutralino --> uds) via the RPV coupling lambda''_112.
Observed exclusion contours on the gluino and neutralino masses in a model where the gluino decays via a virtual top squark to two top quarks and the lightest neutralino, with the neutralino decaying to three light quarks (neutralino --> uds) via the RPV coupling lambda''_112.
Observed exclusion contours on the gluino and neutralino masses in a model where the gluino decays via a virtual top squark to two top quarks and the lightest neutralino, with the neutralino decaying to three light quarks (neutralino --> uds) via the RPV coupling lambda''_112.
Expected exclusion contours on the gluino and neutralino masses in a model where the gluino decays via a virtual top squark to two top quarks and the lightest neutralino, with the neutralino decaying to three light quarks (neutralino --> uds) via the RPV coupling lambda''_112.
Expected exclusion contours on the gluino and neutralino masses in a model where the gluino decays via a virtual top squark to two top quarks and the lightest neutralino, with the neutralino decaying to three light quarks (neutralino --> uds) via the RPV coupling lambda''_112.
Expected exclusion contours on the gluino and neutralino masses in a model where the gluino decays via a virtual top squark to two top quarks and the lightest neutralino, with the neutralino decaying to three light quarks (neutralino --> uds) via the RPV coupling lambda''_112.
Observed exclusion contours on the gluino and stop masses in a model where the gluino decays to a top quark and a top squark, with the top squark decaying to an s-quark and a b-quark via a non-zero lambda''_323 RPV coupling.
Observed exclusion contours on the gluino and stop masses in a model where the gluino decays to a top quark and a top squark, with the top squark decaying to an s-quark and a b-quark via a non-zero lambda''_323 RPV coupling.
Observed exclusion contours on the gluino and stop masses in a model where the gluino decays to a top quark and a top squark, with the top squark decaying to an s-quark and a b-quark via a non-zero lambda''_323 RPV coupling.
Expected exclusion contours on the gluino and stop masses in a model where the gluino decays to a top quark and a top squark, with the top squark decaying to an s-quark and a b-quark via a non-zero lambda''_323 RPV coupling.
Expected exclusion contours on the gluino and stop masses in a model where the gluino decays to a top quark and a top squark, with the top squark decaying to an s-quark and a b-quark via a non-zero lambda''_323 RPV coupling.
Observed exclusion contours on the gluino and neutralino masses in a model with a gluino decaying to two light quarks (q=u,d,s,c) and the neutralino, which then decays to two light quarks and a charged lepton or a neutrino.
Observed exclusion contours on the gluino and neutralino masses in a model with a gluino decaying to two light quarks (q=u,d,s,c) and the neutralino, which then decays to two light quarks and a charged lepton or a neutrino.
Expected exclusion contours on the gluino and neutralino masses in a model with a gluino decaying to two light quarks (q=u,d,s,c) and the neutralino, which then decays to two light quarks and a charged lepton or a neutrino.
Expected exclusion contours on the gluino and neutralino masses in a model with a gluino decaying to two light quarks (q=u,d,s,c) and the neutralino, which then decays to two light quarks and a charged lepton or a neutrino.
Expected exclusion contours on the gluino and neutralino masses in a model with a gluino decaying to two light quarks (q=u,d,s,c) and the neutralino, which then decays to two light quarks and a charged lepton or a neutrino.
Observed exclusion contours on the stop and neutralino masses in a model where the stop decays to a third-generation quark and a higgsino, which decays via the RPV coupling lambda''_323.
Observed exclusion contours on the stop and neutralino masses in a model where the stop decays to a third-generation quark and a higgsino, which decays via the RPV coupling lambda''_323.
Expected exclusion contours on the stop and neutralino masses in a model where the stop decays to a third-generation quark and a higgsino, which decays via the RPV coupling lambda''_323.
Expected exclusion contours on the stop and neutralino masses in a model where the stop decays to a third-generation quark and a higgsino, which decays via the RPV coupling lambda''_323.
Expected exclusion contours on the stop and neutralino masses in a model where the stop decays to a third-generation quark and a higgsino, which decays via the RPV coupling lambda''_323.
Observed exclusion contours on the stop and neutralino masses in a model where the stop decays to a top and a bino-like neutralino, which decays via the RPV coupling lambda''_323.
Observed exclusion contours on the stop and neutralino masses in a model where the stop decays to a top and a bino-like neutralino, which decays via the RPV coupling lambda''_323.
Expected exclusion contours on the stop and neutralino masses in a model where the stop decays to a top and a bino-like neutralino, which decays via the RPV coupling lambda''_323.
Expected exclusion contours on the stop and neutralino masses in a model where the stop decays to a top and a bino-like neutralino, which decays via the RPV coupling lambda''_323.
Observed upper limits on the model cross-section in units of pb as a function of the gluino and neutralino masses in a model where the gluino decays via a virtual top squark to two top quarks and the lightest neutralino, with the neutralino decaying to three light quarks (neutralino --> uds) via the RPV coupling lambda''_112.
Observed upper limits on the model cross-section in units of pb as a function of the gluino and neutralino masses in a model where the gluino decays via a virtual top squark to two top quarks and the lightest neutralino, with the neutralino decaying to three light quarks (neutralino --> uds) via the RPV coupling lambda''_112.
Observed upper limits on the model cross-section in units of pb as a function of the gluino and neutralino masses in a model where the gluino decays via a virtual top squark to two top quarks and the lightest neutralino, with the neutralino decaying to three light quarks (neutralino --> uds) via the RPV coupling lambda''_112.
Observed upper limits on the model cross-section in units of pb as a function of the gluino and stop masses in a model where the gluino decays to a top quark and a top squark, with the top squark decaying to an s-quark and a b-quark via a non-zero lambda''_323 RPV coupling.
Observed upper limits on the model cross-section in units of pb as a function of the gluino and stop masses in a model where the gluino decays to a top quark and a top squark, with the top squark decaying to an s-quark and a b-quark via a non-zero lambda''_323 RPV coupling.
Observed upper limits on the model cross-section in units of pb as a function of the gluino and stop masses in a model where the gluino decays to a top quark and a top squark, with the top squark decaying to an s-quark and a b-quark via a non-zero lambda''_323 RPV coupling.
Observed upper limits on the model cross-section in units of pb as a function of the gluino and neutralino masses in a model with a gluino decaying to two light quarks (q=u,d,s,c) and the neutralino, which then decays to two light quarks and a charged lepton or a neutrino.
Observed upper limits on the model cross-section in units of pb as a function of the gluino and neutralino masses in a model with a gluino decaying to two light quarks (q=u,d,s,c) and the neutralino, which then decays to two light quarks and a charged lepton or a neutrino.
Observed upper limits on the model cross-section in units of pb as a function of the gluino and neutralino masses in a model with a gluino decaying to two light quarks (q=u,d,s,c) and the neutralino, which then decays to two light quarks and a charged lepton or a neutrino.
Observed upper limits on the model cross-section in units of pb as a function of the stop and neutralino masses in a model where the stop decays to a third-generation quark and a higgsino, which decays via the RPV coupling lambda''_323.
Observed upper limits on the model cross-section in units of pb as a function of the stop and neutralino masses in a model where the stop decays to a third-generation quark and a higgsino, which decays via the RPV coupling lambda''_323.
Observed upper limits on the model cross-section in units of pb as a function of the stop and neutralino masses in a model where the stop decays to a third-generation quark and a higgsino, which decays via the RPV coupling lambda''_323.
Observed upper limits on the model cross-section in units of pb as a function of the stop and neutralino masses in a model where the stop decays to a top and a bino-like neutralino, which decays via the RPV coupling lambda''_323.
Observed upper limits on the model cross-section in units of pb as a function of the stop and neutralino masses in a model where the stop decays to a top and a bino-like neutralino, which decays via the RPV coupling lambda''_323.
Observed upper limits on the model cross-section in units of pb as a function of the stop and neutralino masses in a model where the stop decays to a top and a bino-like neutralino, which decays via the RPV coupling lambda''_323.
Acceptance as a function of the gluino and stop masses in a model where the gluino decays to a top quark and a top squark, with the top squark decaying to an s-quark and a b-quark via a non-zero lambda''_323 RPV coupling.
Acceptance as a function of the gluino and stop masses in a model where the gluino decays to a top quark and a top squark, with the top squark decaying to an s-quark and a b-quark via a non-zero lambda''_323 RPV coupling.
Efficiency as a function of the gluino and stop masses in a model where the gluino decays to a top quark and a top squark, with the top squark decaying to an s-quark and a b-quark via a non-zero lambda''_323 RPV coupling.
Efficiency as a function of the gluino and stop masses in a model where the gluino decays to a top quark and a top squark, with the top squark decaying to an s-quark and a b-quark via a non-zero lambda''_323 RPV coupling.
Acceptance as a function of the gluino and neutralino masses in a model with a gluino decaying to two light quarks (q=u,d,s,c) and the neutralino, which then decays to two light quarks and a charged lepton or a neutrino.
Acceptance as a function of the gluino and neutralino masses in a model with a gluino decaying to two light quarks (q=u,d,s,c) and the neutralino, which then decays to two light quarks and a charged lepton or a neutrino.
Acceptance as a function of the gluino and neutralino masses in a model with a gluino decaying to two light quarks (q=u,d,s,c) and the neutralino, which then decays to two light quarks and a charged lepton or a neutrino.
Efficiency as a function of the gluino and neutralino masses in a model with a gluino decaying to two light quarks (q=u,d,s,c) and the neutralino, which then decays to two light quarks and a charged lepton or a neutrino.
Efficiency as a function of the gluino and neutralino masses in a model with a gluino decaying to two light quarks (q=u,d,s,c) and the neutralino, which then decays to two light quarks and a charged lepton or a neutrino.
Cut flow for a model of gluino pair production where the gluino decays to two (u, d, s, c) quarks and the neutralino, which then decays to two (u, d, s, c) quarks and a lepton via a lambda' RPV coupling, where each RPV decay can produce any of the four first and second generation leptons (e, mu, nu_e, nu_mu) with equal probability (m_gluino = 1800 GeV, m_neutralino = 900 GeV). The events are skimmed by requiring at least one electron or muon that satisfies very loose identification criteria, where the lepton satisfies pT > 25 GeV. The efficiency of this cut is considered in the quoted efficiency of the lepton trigger requirement. Selections with negligible inefficiencies on the given sample, such as data quality requirements, are not displayed.
Cut flow for a model of gluino pair production where the gluino decays to two (u, d, s, c) quarks and the neutralino, which then decays to two (u, d, s, c) quarks and a lepton via a lambda' RPV coupling, where each RPV decay can produce any of the four first and second generation leptons (e, mu, nu_e, nu_mu) with equal probability (m_gluino = 1800 GeV, m_neutralino = 900 GeV). The events are skimmed by requiring at least one electron or muon that satisfies very loose identification criteria, where the lepton satisfies pT > 25 GeV. The efficiency of this cut is considered in the quoted efficiency of the lepton trigger requirement. Selections with negligible inefficiencies on the given sample, such as data quality requirements, are not displayed.
Cut flow for a model of gluino pair production where each gluino decays to a top quark and a top squark, with the top squark decaying to an s- and a b- quark via a non-zero lambda''_323 RPV coupling (m_gluino = 1600 GeV, m_stop = 1000 GeV). The events are skimmed by requiring at least one electron or muon that satisfies very loose identification criteria, where the lepton satisfies pT > 25 GeV. The efficiency of this cut is considered in the quoted efficiency of the lepton trigger requirement. Selections with negligible inefficiencies on the given sample, such as data quality requirements, are not displayed.
Cut flow for a model of gluino pair production where each gluino decays to a top quark and a top squark, with the top squark decaying to an s- and a b- quark via a non-zero lambda''_323 RPV coupling (m_gluino = 1600 GeV, m_stop = 1000 GeV). The events are skimmed by requiring at least one electron or muon that satisfies very loose identification criteria, where the lepton satisfies pT > 25 GeV. The efficiency of this cut is considered in the quoted efficiency of the lepton trigger requirement. Selections with negligible inefficiencies on the given sample, such as data quality requirements, are not displayed.
Cut flow for a model of gluino pair production where each gluino decays to a top quark and a top squark, with the top squark decaying to an s- and a b- quark via a non-zero lambda''_323 RPV coupling (m_gluino = 1600 GeV, m_stop = 1000 GeV). The events are skimmed by requiring at least one electron or muon that satisfies very loose identification criteria, where the lepton satisfies pT > 25 GeV. The efficiency of this cut is considered in the quoted efficiency of the lepton trigger requirement. Selections with negligible inefficiencies on the given sample, such as data quality requirements, are not displayed.
Cut flow for a model of gluino pair production where each gluino decays via an off-shell top squark to two top quarks and the lightest neutralino, with the neutralino decaying to three light quarks (neutralino -> uds) via the RPV coupling lambda''_112 (m_gluino = 2000 GeV, m_neutralino = 941 GeV). The events are skimmed by requiring at least one electron or muon that satisfies very loose identification criteria, where the lepton satisfies pT > 25 GeV. The efficiency of this cut is considered in the quoted efficiency of the lepton trigger requirement. Selections with negligible inefficiencies on the given sample, such as data quality requirements, are not displayed.
Cut flow for a model of gluino pair production where each gluino decays via an off-shell top squark to two top quarks and the lightest neutralino, with the neutralino decaying to three light quarks (neutralino -> uds) via the RPV coupling lambda''_112 (m_gluino = 2000 GeV, m_neutralino = 941 GeV). The events are skimmed by requiring at least one electron or muon that satisfies very loose identification criteria, where the lepton satisfies pT > 25 GeV. The efficiency of this cut is considered in the quoted efficiency of the lepton trigger requirement. Selections with negligible inefficiencies on the given sample, such as data quality requirements, are not displayed.
Cut flow for a model of gluino pair production where each gluino decays via an off-shell top squark to two top quarks and the lightest neutralino, with the neutralino decaying to three light quarks (neutralino -> uds) via the RPV coupling lambda''_112 (m_gluino = 2000 GeV, m_neutralino = 941 GeV). The events are skimmed by requiring at least one electron or muon that satisfies very loose identification criteria, where the lepton satisfies pT > 25 GeV. The efficiency of this cut is considered in the quoted efficiency of the lepton trigger requirement. Selections with negligible inefficiencies on the given sample, such as data quality requirements, are not displayed.
Cut flow for a model of right-handed top squark pair production with the top squark decaying to the lightest supersymmetric particle (LSP) which is considered to be purely higgsino. The higgsino-like LSP decays through the non-zero RPV coupling lambda''_323 (m_stop = 975 GeV, m_neutralino = 600 GeV). The events are skimmed by requiring at least one electron or muon that satisfies very loose identification criteria, where the lepton satisfies pT > 25 GeV. The efficiency of this cut is considered in the quoted efficiency of the lepton trigger requirement. Selections with negligible inefficiencies on the given sample, such as data quality requirements, are not displayed.
Cut flow for a model of right-handed top squark pair production with the top squark decaying to the lightest supersymmetric particle (LSP) which is considered to be purely higgsino. The higgsino-like LSP decays through the non-zero RPV coupling lambda''_323 (m_stop = 975 GeV, m_neutralino = 600 GeV). The events are skimmed by requiring at least one electron or muon that satisfies very loose identification criteria, where the lepton satisfies pT > 25 GeV. The efficiency of this cut is considered in the quoted efficiency of the lepton trigger requirement. Selections with negligible inefficiencies on the given sample, such as data quality requirements, are not displayed.
Cut flow for a model of right-handed top squark pair production with the top squark decaying to the lightest supersymmetric particle (LSP) which is considered to be purely higgsino. The higgsino-like LSP decays through the non-zero RPV coupling lambda''_323 (m_stop = 975 GeV, m_neutralino = 600 GeV). The events are skimmed by requiring at least one electron or muon that satisfies very loose identification criteria, where the lepton satisfies pT > 25 GeV. The efficiency of this cut is considered in the quoted efficiency of the lepton trigger requirement. Selections with negligible inefficiencies on the given sample, such as data quality requirements, are not displayed.
This paper presents a search for direct electroweak gaugino or gluino pair production with a chargino nearly mass-degenerate with a stable neutralino. It is based on an integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ of $pp$ collisions at $\sqrt{s} = 13$ TeV collected by the ATLAS experiment at the LHC. The final state of interest is a disappearing track accompanied by at least one jet with high transverse momentum from initial-state radiation or by four jets from the gluino decay chain. The use of short track segments reconstructed from the innermost tracking layers significantly improves the sensitivity to short chargino lifetimes. The results are found to be consistent with Standard Model predictions. Exclusion limits are set at 95% confidence level on the mass of charginos and gluinos for different chargino lifetimes. For a pure wino with a lifetime of about 0.2 ns, chargino masses up to 460 GeV are excluded. For the strong production channel, gluino masses up to 1.65 TeV are excluded assuming a chargino mass of 460 GeV and lifetime of 0.2 ns.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($\tau_{\tilde{\chi}_{1}^{\pm}}$ = 0.2 ns and $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV) in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($\tau_{\tilde{\chi}_{1}^{\pm}}$ = 0.2 ns and $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV) in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($\tau_{\tilde{\chi}_{1}^{\pm}}$ = 0.2 ns and $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV) in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($\tau_{\tilde{\chi}_{1}^{\pm}}$ = 0.2 ns and $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV) in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}} = 500 GeV$) in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}} = 500 GeV$) in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}} = 500 GeV$) in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}} = 500 GeV$) in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}} = 500 GeV$) in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($\tau_{\tilde{\chi}_{1}^{\pm}}$ = 0.2 ns and $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV) in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($\tau_{\tilde{\chi}_{1}^{\pm}}$ = 0.2 ns and $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV) in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($\tau_{\tilde{\chi}_{1}^{\pm}}$ = 0.2 ns and $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV) in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($\tau_{\tilde{\chi}_{1}^{\pm}}$ = 0.2 ns and $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV) in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($\tau_{\tilde{\chi}_{1}^{\pm}}$ = 0.2 ns and $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV) in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}} = 500 GeV$) in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}} = 500 GeV$) in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}} = 500 GeV$) in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}} = 500 GeV$) in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}} = 500 GeV$) in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in strong channel in the high-Emiss region.
Expected exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Expected exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Expected exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Expected exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Expected exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Observed exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Observed exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Observed exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Observed exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Observed exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Expected exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 0.2 ns.
Expected exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 0.2 ns.
Expected exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 0.2 ns.
Expected exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 0.2 ns.
Expected exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 0.2 ns.
Observed exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 0.2 ns.
Observed exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 0.2 ns.
Observed exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 0.2 ns.
Observed exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 0.2 ns.
Observed exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 0.2 ns.
Expected exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 1.0 ns.
Expected exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 1.0 ns.
Expected exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 1.0 ns.
Expected exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 1.0 ns.
Expected exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 1.0 ns.
Observed exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 1.0 ns.
Observed exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 1.0 ns.
Observed exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 1.0 ns.
Observed exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 1.0 ns.
Observed exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 1.0 ns.
Expected exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Expected exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Expected exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Expected exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Expected exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Observed exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Observed exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Observed exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Observed exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Observed exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Model dependent upper limits on cross-section (fb) for the electroweak production are shown by grey numbers in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Model dependent upper limits on cross-section (pb) for the electroweak production are shown by grey numbers in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Model dependent upper limits on cross-section (pb) for the electroweak production are shown by grey numbers in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Model dependent upper limits on cross-section (pb) for the electroweak production are shown by grey numbers in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Model dependent upper limits on cross-section (pb) for the electroweak production are shown by grey numbers in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Total acceptance $\times$ efficiency of the electroweak channel. The total signal acceptance $\times$ efficiency is defined as the probability of an event passing the signal region selection when an electroweak gaugino pair is produced in a pp collision.
Total acceptance $\times$ efficiency of the electroweak channel. The total signal acceptance $\times$ efficiency is defined as the probability of an event passing the signal region selection when an electroweak gaugino pair is produced in a pp collision.
Total acceptance $\times$ efficiency of the electroweak channel. The total signal acceptance $\times$ efficiency is defined as the probability of an event passing the signal region selection when an electroweak gaugino pair is produced in a pp collision.
Total acceptance $\times$ efficiency of the electroweak channel. The total signal acceptance $\times$ efficiency is defined as the probability of an event passing the signal region selection when an electroweak gaugino pair is produced in a pp collision.
Total acceptance $\times$ efficiency of the electroweak channel. The total signal acceptance $\times$ efficiency is defined as the probability of an event passing the signal region selection when an electroweak gaugino pair is produced in a pp collision.
Total acceptance $\times$ efficiency of the strong channel. In white regions, no simulation sample is available. The left-upper triangle region is not allowed kinematically in wino-LSP scenarios. The total signal acceptance $\times$ efficiency is calculated relative to events in which the gluinos decay into electroweak gaugino pairs.
Total acceptance $\times$ efficiency of the strong channel. In white regions, no simulation sample is available. The left-upper triangle region is not allowed kinematically in wino-LSP scenarios. The total signal acceptance $\times$ efficiency is calculated relative to events in which the gluinos decay into electroweak gaugino pairs.
Total acceptance $\times$ efficiency of the strong channel. In white regions, no simulation sample is available. The left-upper triangle region is not allowed kinematically in wino-LSP scenarios. The total signal acceptance $\times$ efficiency is calculated relative to events in which the gluinos decay into electroweak gaugino pairs.
Total acceptance $\times$ efficiency of the strong channel. In white regions, no simulation sample is available. The left-upper triangle region is not allowed kinematically in wino-LSP scenarios. The total signal acceptance $\times$ efficiency is calculated relative to events in which the gluinos decay into electroweak gaugino pairs.
Total acceptance $\times$ efficiency of the strong channel. In white regions, no simulation sample is available. The left-upper triangle region is not allowed kinematically in wino-LSP scenarios. The total signal acceptance $\times$ efficiency is calculated relative to events in which the gluinos decay into electroweak gaugino pairs.
The generator-level acceptance after reconstruction, for selecting and reconstructing charginos as a function of the chargino $eta$ and chargino decay radius (at generator level).
The generator-level acceptance for charginos produced in the electroweak channel as a function of the chargino $eta$ and chargino decay radius (at generator level).
The generator-level acceptance for charginos produced in the electroweak channel as a function of the chargino $eta$ and chargino decay radius (at generator level).
The generator-level acceptance for charginos produced in the electroweak channel as a function of the chargino $eta$ and chargino decay radius (at generator level).
The generator-level acceptance for charginos produced in the electroweak channel as a function of the chargino $eta$ and chargino decay radius (at generator level).
The generator-level acceptance $\times$ efficiency after reconstruction, for selecting and reconstructing charginos as a function of the chargino $\eta$ and chargino decay radius (at generator level). The acceptance $\times$ efficiency after reconstruction is the probability of a signal event, which passes all the event-level requirements, passing all the track/tracklet requirements after reconstruction.
The acceptance $\times$ efficiency after reconstruction, for selecting and reconstructing charginos produced in the electroweak channel as a function of the chargino $\eta$ and chargino decay radius (at generator level). The acceptance $\times$ efficiency after reconstruction is the probability of a signal event, which passes all the event-level requirements, passing all the track/tracklet requirements after reconstruction.
The acceptance $\times$ efficiency after reconstruction, for selecting and reconstructing charginos produced in the electroweak channel as a function of the chargino $\eta$ and chargino decay radius (at generator level). The acceptance $\times$ efficiency after reconstruction is the probability of a signal event, which passes all the event-level requirements, passing all the track/tracklet requirements after reconstruction.
The acceptance $\times$ efficiency after reconstruction, for selecting and reconstructing charginos produced in the electroweak channel as a function of the chargino $\eta$ and chargino decay radius (at generator level). The acceptance $\times$ efficiency after reconstruction is the probability of a signal event, which passes all the event-level requirements, passing all the track/tracklet requirements after reconstruction.
The acceptance $\times$ efficiency after reconstruction, for selecting and reconstructing charginos produced in the electroweak channel as a function of the chargino $\eta$ and chargino decay radius (at generator level). The acceptance $\times$ efficiency after reconstruction is the probability of a signal event, which passes all the event-level requirements, passing all the track/tracklet requirements after reconstruction.
The generator-level acceptance after reconstruction, for selecting and reconstructing charginos as a function of the chargino $\eta$ and chargino decay radius (at generator level).
The generator-level acceptance for charginos produced in the strong channel as a function of the chargino $\eta$ and chargino decay radius (at generator level).
The generator-level acceptance for charginos produced in the strong channel as a function of the chargino $\eta$ and chargino decay radius (at generator level).
The generator-level acceptance for charginos produced in the strong channel as a function of the chargino $\eta$ and chargino decay radius (at generator level).
The generator-level acceptance for charginos produced in the strong channel as a function of the chargino $\eta$ and chargino decay radius (at generator level).
The generator-level acceptance $\times$ efficiency after reconstruction, for selecting and reconstructing charginos as a function of the chargino $\eta$ and chargino decay radius (at generator level). The acceptance $\times$ efficiency after reconstruction is the probability of a signal event, which passes all the event-level requirements, passing all the track/tracklet requirements after reconstruction.
The acceptance $\times$ efficiency after reconstruction, for selecting and reconstructing charginos produced in the strong channel as a function of the chargino $\eta$ and chargino decay radius (at generator level). The acceptance $\times$ efficiency after reconstruction is the probability of a signal event, which passes all the event-level requirements, passing all the track/tracklet requirements after reconstruction.
The acceptance $\times$ efficiency after reconstruction, for selecting and reconstructing charginos produced in the strong channel as a function of the chargino $\eta$ and chargino decay radius (at generator level). The acceptance $\times$ efficiency after reconstruction is the probability of a signal event, which passes all the event-level requirements, passing all the track/tracklet requirements after reconstruction.
The acceptance $\times$ efficiency after reconstruction, for selecting and reconstructing charginos produced in the strong channel as a function of the chargino $\eta$ and chargino decay radius (at generator level). The acceptance $\times$ efficiency after reconstruction is the probability of a signal event, which passes all the event-level requirements, passing all the track/tracklet requirements after reconstruction.
The acceptance $\times$ efficiency after reconstruction, for selecting and reconstructing charginos produced in the strong channel as a function of the chargino $\eta$ and chargino decay radius (at generator level). The acceptance $\times$ efficiency after reconstruction is the probability of a signal event, which passes all the event-level requirements, passing all the track/tracklet requirements after reconstruction.
Summary of the selection criteria, and the corresponding observed number of events in data as well as the expected number of signal events in simulation for two benchmark models: a chargino produced in direct electroweak production with ($m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (400 GeV, 0.2 ns) in the high-Emiss region. The expected number of signal events is normalised to 36.1 fb${}^{-1}$. The signal selection efficiencies are also shown in parentheses. The first row shows the number of events after the application of detector and data quality conditions. Requirements below the dashed line are applied to tracks and tracklets.
Summary of the selection criteria, and the corresponding observed number of events in data as well as the expected number of signal events in simulation for two benchmark models: a chargino produced in direct electroweak production with ($m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (400 GeV, 0.2 ns) in the high-Emiss region. The expected number of signal events is normalised to 36.1 fb${}^{-1}$. The signal selection efficiencies are also shown in parentheses. The first row shows the number of events after the application of detector and data quality conditions. Requirements below the dashed line are applied to tracks and tracklets.
Summary of the selection criteria, and the corresponding observed number of events in data as well as the expected number of signal events in simulation for two benchmark models: a chargino produced in direct electroweak production with ($m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (400 GeV, 0.2 ns) in the high-Emiss region. The expected number of signal events is normalised to 36.1 fb${}^{-1}$. The signal selection efficiencies are also shown in parentheses. The first row shows the number of events after the application of detector and data quality conditions. Requirements below the dashed line are applied to tracks and tracklets.
Summary of the selection criteria, and the corresponding observed number of events in data as well as the expected number of signal events in simulation for two benchmark models: a chargino produced in direct electroweak production with ($m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (400 GeV, 0.2 ns) in the high-Emiss region. The expected number of signal events is normalised to 36.1 fb${}^{-1}$. The signal selection efficiencies are also shown in parentheses. The first row shows the number of events after the application of detector and data quality conditions. Requirements below the dashed line are applied to tracks and tracklets.
Summary of the selection criteria, and the corresponding observed number of events in data as well as the expected number of signal events in simulation for two benchmark models: a chargino produced in direct electroweak production with ($m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (400 GeV, 0.2 ns) in the high-Emiss region. The expected number of signal events is normalised to 36.1 fb${}^{-1}$. The signal selection efficiencies are also shown in parentheses. The first row shows the number of events after the application of detector and data quality conditions. Requirements below the dashed line are applied to tracks and tracklets.
Summary of the selection criteria, and the corresponding observed number of events in data as well as the expected number of signal events in simulation for two benchmark models: a chargino produced in the strong channel with ($m_{\tilde{g}}$, $m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (1600 GeV, 500 GeV, 0.2 ns) in the high-Emiss region. The expected number of signal events is normalised to 36.1 fb${}^{-1}$. The signal selection efficiencies are also shown in parentheses. The first row shows the number of events after the application of detector and data quality conditions. Requirements below the dashed line are applied to tracks and tracklets.
Summary of the selection criteria, and the corresponding observed number of events in data as well as the expected number of signal events in simulation for two benchmark models: a chargino produced in the strong channel with ($m_{\tilde{g}}$, $m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (1600 GeV, 500 GeV, 0.2 ns) in the high-Emiss region. The expected number of signal events is normalised to 36.1 fb${}^{-1}$. The signal selection efficiencies are also shown in parentheses. The first row shows the number of events after the application of detector and data quality conditions. Requirements below the dashed line are applied to tracks and tracklets.
Summary of the selection criteria, and the corresponding observed number of events in data as well as the expected number of signal events in simulation for two benchmark models: a chargino produced in the strong channel with ($m_{\tilde{g}}$, $m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (1600 GeV, 500 GeV, 0.2 ns) in the high-Emiss region. The expected number of signal events is normalised to 36.1 fb${}^{-1}$. The signal selection efficiencies are also shown in parentheses. The first row shows the number of events after the application of detector and data quality conditions. Requirements below the dashed line are applied to tracks and tracklets.
Summary of the selection criteria, and the corresponding observed number of events in data as well as the expected number of signal events in simulation for two benchmark models: a chargino produced in the strong channel with ($m_{\tilde{g}}$, $m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (1600 GeV, 500 GeV, 0.2 ns) in the high-Emiss region. The expected number of signal events is normalised to 36.1 fb${}^{-1}$. The signal selection efficiencies are also shown in parentheses. The first row shows the number of events after the application of detector and data quality conditions. Requirements below the dashed line are applied to tracks and tracklets.
Summary of the selection criteria, and the corresponding observed number of events in data as well as the expected number of signal events in simulation for two benchmark models: a chargino produced in the strong channel with ($m_{\tilde{g}}$, $m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (1600 GeV, 500 GeV, 0.2 ns) in the high-Emiss region. The expected number of signal events is normalised to 36.1 fb${}^{-1}$. The signal selection efficiencies are also shown in parentheses. The first row shows the number of events after the application of detector and data quality conditions. Requirements below the dashed line are applied to tracks and tracklets.
The event and tracklet generator-level acceptance and selection efficiency for a few electroweak signal models studied in this search. The last column shows the probability ($P$) for a reconstructed tracklet to have $p_{T}$ greater than 100 GeV.
The event and tracklet generator-level acceptance and selection efficiency for a few electroweak signal models studied in this search. The last column shows the probability ($P$) for a reconstructed tracklet to have $p_{T}$ greater than 100 GeV.
The event and tracklet generator-level acceptance and selection efficiency for a few electroweak signal models studied in this search. The last column shows the probability ($P$) for a reconstructed tracklet to have $p_{T}$ greater than 100 GeV.
The event and tracklet generator-level acceptance and selection efficiency for a few electroweak signal models studied in this search. The last column shows the probability ($P$) for a reconstructed tracklet to have $p_{T}$ greater than 100 GeV.
The event and tracklet generator-level acceptance and selection efficiency for a few electroweak signal models studied in this search. The last column shows the probability ($P$) for a reconstructed tracklet to have $p_{T}$ greater than 100 GeV.
The event and tracklet generator-level acceptance and selection efficiency for a few strong signal models studied in this search. The last column shows the probability ($P$) for a reconstructed tracklet to have $p_{T}$ greater than 100 GeV.
The event and tracklet generator-level acceptance and selection efficiency for a few strong signal models studied in this search. The last column shows the probability ($P$) for a reconstructed tracklet to have $p_{T}$ greater than 100 GeV.
The event and tracklet generator-level acceptance and selection efficiency for a few strong signal models studied in this search. The last column shows the probability ($P$) for a reconstructed tracklet to have $p_{T}$ greater than 100 GeV.
The event and tracklet generator-level acceptance and selection efficiency for a few strong signal models studied in this search. The last column shows the probability ($P$) for a reconstructed tracklet to have $p_{T}$ greater than 100 GeV.
The event and tracklet generator-level acceptance and selection efficiency for a few strong signal models studied in this search. The last column shows the probability ($P$) for a reconstructed tracklet to have $p_{T}$ greater than 100 GeV.
Systematic uncertainties in the signal event yields at $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV for the electroweak channel and at $m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}}$ = 500 GeV for the strong channel. The lifetime of the chargino is not relevant here. The uncertainty in the cross-section of the strong production is large due to the large effect from the PDF uncertainty.
Systematic uncertainties in the signal event yields at $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV for the electroweak channel and at $m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}}$ = 500 GeV for the strong channel. The lifetime of the chargino is not relevant here. The uncertainty in the cross-section of the strong production is large due to the large effect from the PDF uncertainty.
Systematic uncertainties in the signal event yields at $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV for the electroweak channel and at $m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}}$ = 500 GeV for the strong channel. The lifetime of the chargino is not relevant here. The uncertainty in the cross-section of the strong production is large due to the large effect from the PDF uncertainty.
Systematic uncertainties in the signal event yields at $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV for the electroweak channel and at $m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}}$ = 500 GeV for the strong channel. The lifetime of the chargino is not relevant here. The uncertainty in the cross-section of the strong production is large due to the large effect from the PDF uncertainty.
Systematic uncertainties in the signal event yields at $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV for the electroweak channel and at $m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}}$ = 500 GeV for the strong channel. The lifetime of the chargino is not relevant here. The uncertainty in the cross-section of the strong production is large due to the large effect from the PDF uncertainty.
Observed events, expected background for null signal, and expected signal yields for two benchmark models: electroweak channel with ($m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (400 GeV, 0.2 ns) and strong channel with ($m_{\tilde{g}}$, $m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (1600 GeV, 500 GeV, 0.2 ns) in the high-Emiss region. Also shown are the probability of a background-only experiment being more signal-like than observed ($p_0$) and the upper limit on the model-independent visible cross-section at 95\% CL. The uncertainty in the total background yield is different from the sum of uncertainties in quadrature due to anticorrelation between different backgrounds.
Observed events, expected background for null signal, and expected signal yields for two benchmark models: electroweak channel with ($m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (400 GeV, 0.2 ns) and strong channel with ($m_{\tilde{g}}$, $m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (1600 GeV, 500 GeV, 0.2 ns) in the high-Emiss region. Also shown are the probability of a background-only experiment being more signal-like than observed ($p_0$) and the upper limit on the model-independent visible cross-section at 95\% CL. The uncertainty in the total background yield is different from the sum of uncertainties in quadrature due to anti-correlation between different backgrounds.
Observed events, expected background for null signal, and expected signal yields for two benchmark models: electroweak channel with ($m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (400 GeV, 0.2 ns) and strong channel with ($m_{\tilde{g}}$, $m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (1600 GeV, 500 GeV, 0.2 ns) in the high-Emiss region. Also shown are the probability of a background-only experiment being more signal-like than observed ($p_0$) and the upper limit on the model-independent visible cross-section at 95\% CL. The uncertainty in the total background yield is different from the sum of uncertainties in quadrature due to anti-correlation between different backgrounds.
Observed events, expected background for null signal, and expected signal yields for two benchmark models: electroweak channel with ($m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (400 GeV, 0.2 ns) and strong channel with ($m_{\tilde{g}}$, $m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (1600 GeV, 500 GeV, 0.2 ns) in the high-Emiss region. Also shown are the probability of a background-only experiment being more signal-like than observed ($p_0$) and the upper limit on the model-independent visible cross-section at 95\% CL. The uncertainty in the total background yield is different from the sum of uncertainties in quadrature due to anti-correlation between different backgrounds.
Observed events, expected background for null signal, and expected signal yields for two benchmark models: electroweak channel with ($m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (400 GeV, 0.2 ns) and strong channel with ($m_{\tilde{g}}$, $m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (1600 GeV, 500 GeV, 0.2 ns) in the high-Emiss region. Also shown are the probability of a background-only experiment being more signal-like than observed ($p_0$) and the upper limit on the model-independent visible cross-section at 95\% CL. The uncertainty in the total background yield is different from the sum of uncertainties in quadrature due to anti-correlation between different backgrounds.
Effects of systematic uncertainties on the signal exclusion significance at $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV for the electroweak channel and at $m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}}$ = 500 GeV for the strong channel. The lifetime of the chargino is not relevant here. Effects of uncertainties on the fake-tracklet background is smaller in the strong channel analysis because the estimated number of the fake-tracket background events is small.
Effects of systematic uncertainties on the signal exclusion significance at $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV for the electroweak channel and at $m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}}$ = 500 GeV for the strong channel. The lifetime of the chargino is not relevant here. Effects of uncertainties on the fake-tracklet background is smaller in the strong channel analysis because the estimated number of the fake-tracklet background events is small.
Effects of systematic uncertainties on the signal exclusion significance at $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV for the electroweak channel and at $m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}}$ = 500 GeV for the strong channel. The lifetime of the chargino is not relevant here. Effects of uncertainties on the fake-tracklet background is smaller in the strong channel analysis because the estimated number of the fake-tracklet background events is small.
Effects of systematic uncertainties on the signal exclusion significance at $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV for the electroweak channel and at $m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}}$ = 500 GeV for the strong channel. The lifetime of the chargino is not relevant here. Effects of uncertainties on the fake-tracklet background is smaller in the strong channel analysis because the estimated number of the fake-tracklet background events is small.
Effects of systematic uncertainties on the signal exclusion significance at $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV for the electroweak channel and at $m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}}$ = 500 GeV for the strong channel. The lifetime of the chargino is not relevant here. Effects of uncertainties on the fake-tracklet background is smaller in the strong channel analysis because the estimated number of the fake-tracklet background events is small.
Cross-section upper limits for the strong production, presented in unit of fb. Left-upper triangle region is unphysical because the wino mass is larger than the gluino mass.
Cross-section upper limits for the strong production, presented in unit of fb. Left-upper triangle region is unphysical because the wino mass is larger than the gluino mass.
Cross-section upper limits for the strong production, presented in unit of fb. Left-upper triangle region is unphysical because the wino mass is larger than the gluino mass.
Cross-section upper limits for the strong production, presented in unit of fb. Left-upper triangle region is unphysical because the wino mass is larger than the gluino mass.
A search for charged Higgs bosons decaying into $W^\pm W^\pm$ or $W^\pm Z$ bosons is performed, involving experimental signatures with two leptons of the same charge, or three or four leptons with a variety of charge combinations, missing transverse momentum and jets. A data sample of proton-proton collisions at a centre-of-mass energy of 13 TeV recorded with the ATLAS detector at the Large Hadron Collider between 2015 and 2018 is used. The data correspond to a total integrated luminosity of 139 fb$^{-1}$. The search is guided by a type-II seesaw model that extends the scalar sector of the Standard Model with a scalar triplet, leading to a phenomenology that includes doubly and singly charged Higgs bosons. Two scenarios are explored, corresponding to the pair production of doubly charged $H^{\pm\pm}$ bosons, or the associated production of a doubly charged $H^{\pm\pm}$ boson and a singly charged $H^\pm$ boson. No significant deviations from the Standard Model predictions are observed. $H^{\pm\pm}$ bosons are excluded at 95% confidence level up to 350 GeV and 230 GeV for the pair and associated production modes, respectively.
Measurements of the Standard Model Higgs boson decaying into a $b\bar{b}$ pair and produced in association with a $W$ or $Z$ boson decaying into leptons, using proton-proton collision data collected between 2015 and 2018 by the ATLAS detector, are presented. The measurements use collisions produced by the Large Hadron Collider at a centre-of-mass energy of $\sqrt{s} = $13 TeV, corresponding to an integrated luminosity of 139 fb$^{-1}$. The production of a Higgs boson in association with a $W$ or $Z$ boson is established with observed (expected) significances of 4.0 (4.1) and 5.3 (5.1) standard deviations, respectively. Cross-sections of associated production of a Higgs boson decaying into bottom quark pairs with an electroweak gauge boson, $W$ or $Z$, decaying into leptons are measured as a function of the gauge boson transverse momentum in kinematic fiducial volumes. The cross-section measurements are all consistent with the Standard Model expectations, and the total uncertainties vary from 30% in the high gauge boson transverse momentum regions to 85% in the low regions. Limits are subsequently set on the parameters of an effective Lagrangian sensitive to modifications of the $WH$ and $ZH$ processes as well as the Higgs boson decay into $b\bar{b}$.
Best-fit values and uncertainties for $VH, V\rightarrow\mathrm{leptons}$ for the cross-section times the $H\rightarrow b\bar{b}$ branching fraction, in the reduced stage-1.2 simplififed template cross-sections (STXS) scheme. The SM predictions for each region is also shown. They are obtained from the samples of simulated events scaled to the inclusive cross-sections calculated at NNLO(QCD)+NLO(EW) accuracy for the $qq\rightarrow WH$ and $qq\rightarrow ZH$ processes, and at NLO+NLL accuracy for the $gg\rightarrow ZH$ process. The contributions to the total uncertainty in the measurements from statistical (Stat.) or systematic uncertainties in the signal modelling (Th. sig.), background modelling (Th. bkg.) and in experimental performance (Exp.) are given separately. All leptonic decays of the $V$ bosons (including those to $\tau$ leptons, $\ell = e, \mu, \tau$) are considered.
Observed correlations between the measured reduced stage-1.2 simplified template $VH, H \rightarrow b\bar{b}$ cross-sections (STXS), including both the statistical and systematic uncertainties. All leptonic decays of the $V$ bosons (including those to $\tau$ leptons, $\ell = e, \mu, \tau$) are considered.
Linear combination of Wilson coefficients corresponding to SMEFT operators in the Warsaw basis for which this analysis provides orthogonal constraints (eigenvectors). Eigenvalues are shown for each eigenvector, which provides a measure of the experimental sensitivity to that linear combination. The modifications to the $qq\rightarrow ZH$ and $qq\rightarrow WH$ processes due to SMEFT operators are computed at LO, and changes to the $gg\rightarrow ZH$ process are neglected.
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