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The factor of four increase in the LHC luminosity, from $0.5\times 10^{34}\,\textrm{cm}^{-2}\textrm{s}^{-1}$ to $2.0\times 10^{34}\textrm{cm}^{-2}\textrm{s}^{-1}$, and the corresponding increase in pile-up collisions during the 2015-2018 data-taking period, presented a challenge for ATLAS to trigger on missing transverse momentum. The output data rate at fixed threshold typically increases exponentially with the number of pile-up collisions, so the legacy algorithms from previous LHC data-taking periods had to be tuned and new approaches developed to maintain the high trigger efficiency achieved in earlier operations. A study of the trigger performance and comparisons with simulations show that these changes resulted in event selection efficiencies of >98% for this period, meeting and in some cases exceeding the performance of similar triggers in earlier run periods, while at the same time keeping the necessary bandwidth within acceptable limits.
A comparison of the measured cell $E_T^{miss}$ distribution with that predicted by the two-component model for two pile-up scenarios. The magenta points extend the measured distribution using L1 $E_T^{miss} > 30\,$GeV and L1 $E_T^{miss} > 50\,$GeV data. The red curve is the prediction from the calorimeter-resolution part of the model. The green curve is the high $E_T^{miss}$ tail's probability distribution for the mean number of $pp$ interactions $\mu$ in each figure. The blue curve is the full model prediction computed by combining the $E_T^{miss}$ from these two individual sources shown in red and green, each calculated for $\mu=\langle\mu\rangle$. The black points show the unbiased $E_T^{miss}$ distribution measured in data. Corresponds to a prediction for $\langle\mu\rangle = 25$.
A comparison of the measured cell $E_T^{miss}$ distribution with that predicted by the two-component model for two pile-up scenarios. The magenta points extend the measured distribution using L1 $E_T^{miss} > 30\,$GeV and L1 $E_T^{miss} > 50\,$GeV data. The red curve is the prediction from the calorimeter-resolution part of the model. The green curve is the high $E_T^{miss}$ tail's probability distribution for the mean number of $pp$ interactions $\mu$ in each figure. The blue curve is the full model prediction computed by combining the $E_T^{miss}$ from these two individual sources shown in red and green, each calculated for $\mu=\langle\mu\rangle$. The black points show the unbiased $E_T^{miss}$ distribution measured in data. Corresponds to a prediction for $\langle\mu\rangle = 25$.
A comparison of the measured cell $E_T^{miss}$ distribution with that predicted by the two-component model for two pile-up scenarios. The magenta points extend the measured distribution using L1 $E_T^{miss} > 30\,$GeV and L1 $E_T^{miss} > 50\,$GeV data. The red curve is the prediction from the calorimeter-resolution part of the model. The green curve is the high $E_T^{miss}$ tail's probability distribution for the mean number of $pp$ interactions $\mu$ in each figure. The blue curve is the full model prediction computed by combining the $E_T^{miss}$ from these two individual sources shown in red and green, each calculated for $\mu=\langle\mu\rangle$. The black points show the unbiased $E_T^{miss}$ distribution measured in data. Corresponds to a prediction for $\langle\mu\rangle = 55$.
A comparison of the measured cell $E_T^{miss}$ distribution with that predicted by the two-component model for two pile-up scenarios. The magenta points extend the measured distribution using L1 $E_T^{miss} > 30\,$GeV and L1 $E_T^{miss} > 50\,$GeV data. The red curve is the prediction from the calorimeter-resolution part of the model. The green curve is the high $E_T^{miss}$ tail's probability distribution for the mean number of $pp$ interactions $\mu$ in each figure. The blue curve is the full model prediction computed by combining the $E_T^{miss}$ from these two individual sources shown in red and green, each calculated for $\mu=\langle\mu\rangle$. The black points show the unbiased $E_T^{miss}$ distribution measured in data. Corresponds to a prediction for $\langle\mu\rangle = 55$.
A comparison of the measured cell $E_T^{miss}$ distribution with that predicted by the two-component model for two pile-up scenarios. The magenta points extend the measured distribution using L1 $E_T^{miss} > 30\,$GeV and L1 $E_T^{miss} > 50\,$GeV data. The red curve is the prediction from the calorimeter-resolution part of the model. The green curve is the high $E_T^{miss}$ tail's probability distribution for the mean number of $pp$ interactions $\mu$ in each figure. The blue curve is the full model prediction computed by combining the $E_T^{miss}$ from these two individual sources shown in red and green, each calculated for $\mu=\langle\mu\rangle$. The black points show the unbiased $E_T^{miss}$ distribution measured in data. Corresponds to a prediction for $\langle\mu\rangle = 55$.
The $E_T^{miss}$ model predicted trigger rate as a function of $\mu$ for the cell $E_T^{miss}$ algorithm with a threshold of $80\,$GeV and $120\,$GeV, assuming no additional pile-up mitigation.
The efficiencies in the plot are shown for events satisfying a $Z\rightarrow\mu\mu$ selection and with $p_T(\mu\mu)$ larger than $150\,$GeV vs pile-up for each of the four years of data taking.
The L1 $E_T^{miss}$ trigger rate as a function of $\langle\mu\rangle$ for runs in three different periods ($\alpha$, $\beta$, $\gamma$) in the year 2017.
The L1 $E_T^{miss}$ trigger rate as a function of $\langle\mu\rangle$ for runs in three different periods ($\alpha$, $\beta$, $\gamma$) in the year 2017.
The L1 $E_T^{miss}$ trigger rate as a function of $\langle\mu\rangle$ for runs in three different periods ($\alpha$, $\beta$, $\gamma$) in the year 2017.
Background acceptance vs signal efficiency for each of four individual HLT $E_T^{miss}$ algorithms for a $Z\rightarrow\mu\mu$ selection with $p_T(\mu\mu) > 175\,$GeV for data recorded in the year 2017. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger. $0\leq\langle\mu\rangle < 20$.
Background acceptance vs signal efficiency for each of four individual HLT $E_T^{miss}$ algorithms for a $Z\rightarrow\mu\mu$ selection with $p_T(\mu\mu) > 175\,$GeV for data recorded in the year 2017. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger. $0\leq\langle\mu\rangle < 20$.
Background acceptance vs signal efficiency for each of four individual HLT $E_T^{miss}$ algorithms for a $Z\rightarrow\mu\mu$ selection with $p_T(\mu\mu) > 175\,$GeV for data recorded in the year 2017. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger. $0\leq\langle\mu\rangle < 20$.
Background acceptance vs signal efficiency for each of four individual HLT $E_T^{miss}$ algorithms for a $Z\rightarrow\mu\mu$ selection with $p_T(\mu\mu) > 175\,$GeV for data recorded in the year 2017. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger. $0\leq\langle\mu\rangle < 20$.
Background acceptance vs signal efficiency for each of four individual HLT $E_T^{miss}$ algorithms for a $Z\rightarrow\mu\mu$ selection with $p_T(\mu\mu) > 175\,$GeV for data recorded in the year 2017. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger. $0\leq\langle\mu\rangle < 20$.
Background acceptance vs signal efficiency for each of four individual HLT $E_T^{miss}$ algorithms for a $Z\rightarrow\mu\mu$ selection with $p_T(\mu\mu) > 175\,$GeV for data recorded in the year 2017. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger. $20\leq\langle\mu\rangle < 30$.
Background acceptance vs signal efficiency for each of four individual HLT $E_T^{miss}$ algorithms for a $Z\rightarrow\mu\mu$ selection with $p_T(\mu\mu) > 175\,$GeV for data recorded in the year 2017. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger. $20\leq\langle\mu\rangle < 30$.
Background acceptance vs signal efficiency for each of four individual HLT $E_T^{miss}$ algorithms for a $Z\rightarrow\mu\mu$ selection with $p_T(\mu\mu) > 175\,$GeV for data recorded in the year 2017. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger. $20\leq\langle\mu\rangle < 30$.
Background acceptance vs signal efficiency for each of four individual HLT $E_T^{miss}$ algorithms for a $Z\rightarrow\mu\mu$ selection with $p_T(\mu\mu) > 175\,$GeV for data recorded in the year 2017. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger. $20\leq\langle\mu\rangle < 30$.
Background acceptance vs signal efficiency for each of four individual HLT $E_T^{miss}$ algorithms for a $Z\rightarrow\mu\mu$ selection with $p_T(\mu\mu) > 175\,$GeV for data recorded in the year 2017. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger. $20\leq\langle\mu\rangle < 30$.
Background acceptance vs signal efficiency for each of four individual HLT $E_T^{miss}$ algorithms for a $Z\rightarrow\mu\mu$ selection with $p_T(\mu\mu) > 175\,$GeV for data recorded in the year 2017. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger. $30\leq\langle\mu\rangle < 40$.
Background acceptance vs signal efficiency for each of four individual HLT $E_T^{miss}$ algorithms for a $Z\rightarrow\mu\mu$ selection with $p_T(\mu\mu) > 175\,$GeV for data recorded in the year 2017. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger. $30\leq\langle\mu\rangle < 40$.
Background acceptance vs signal efficiency for each of four individual HLT $E_T^{miss}$ algorithms for a $Z\rightarrow\mu\mu$ selection with $p_T(\mu\mu) > 175\,$GeV for data recorded in the year 2017. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger. $30\leq\langle\mu\rangle < 40$.
Background acceptance vs signal efficiency for each of four individual HLT $E_T^{miss}$ algorithms for a $Z\rightarrow\mu\mu$ selection with $p_T(\mu\mu) > 175\,$GeV for data recorded in the year 2017. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger. $40\leq\langle\mu\rangle$.
Background acceptance vs signal efficiency for each of four individual HLT $E_T^{miss}$ algorithms for a $Z\rightarrow\mu\mu$ selection with $p_T(\mu\mu) > 175\,$GeV for data recorded in the year 2017. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger. $40\leq\langle\mu\rangle$.
Background acceptance vs signal efficiency for each of four individual HLT $E_T^{miss}$ algorithms for a $Z\rightarrow\mu\mu$ selection with $p_T(\mu\mu) > 175\,$GeV for data recorded in the year 2017. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger. $40\leq\langle\mu\rangle$.
Background acceptance vs signal efficiency for each of four individual HLT $E_T^{miss}$ algorithms for a $Z\rightarrow\mu\mu$ selection with $p_T(\mu\mu) > 175\,$GeV for data recorded in the year 2017. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger. $40\leq\langle\mu\rangle$.
Background acceptance vs signal efficiency for each of four individual HLT $E_T^{miss}$ algorithms for a $Z\rightarrow\mu\mu$ selection with $p_T(\mu\mu) > 175\,$GeV for data recorded in the year 2017. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger. $40\leq\langle\mu\rangle$.
Relative background acceptance fraction vs. relative efficiency for two different $p_T(\mu\mu)>150\,$GeV threshold for data recorded in the year 2018. Two of the curves show the performance of the stand-alone cell algorithm and the stand-alone pufit algorithm. The other two show combined algorithms each formed by requiring that the event satisfy both a fixed threshold (either 65 GeV or 70 GeV as shown in the legend) for the cell algorithm and a pufit threshold which varies along the curve. In each plot the background acceptance fractions and the efficiencies are relative to those of the pufit $E_T^{miss} > 110\,$GeV trigger and thus can be greater than one. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger while the cross indicates the performance of the combined (pufit $E_T^{miss}>110\,$GeV and cell $E_T^{miss}>50\,$GeV) trigger.
Relative background acceptance fraction vs. relative efficiency for two different $p_T(\mu\mu)>150\,$GeV threshold for data recorded in the year 2018. Two of the curves show the performance of the stand-alone cell algorithm and the stand-alone pufit algorithm. The other two show combined algorithms each formed by requiring that the event satisfy both a fixed threshold (either 65 GeV or 70 GeV as shown in the legend) for the cell algorithm and a pufit threshold which varies along the curve. In each plot the background acceptance fractions and the efficiencies are relative to those of the pufit $E_T^{miss} > 110\,$GeV trigger and thus can be greater than one. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger while the cross indicates the performance of the combined (pufit $E_T^{miss}>110\,$GeV and cell $E_T^{miss}>50\,$GeV) trigger.
Relative background acceptance fraction vs. relative efficiency for two different $p_T(\mu\mu)>150\,$GeV threshold for data recorded in the year 2018. Two of the curves show the performance of the stand-alone cell algorithm and the stand-alone pufit algorithm. The other two show combined algorithms each formed by requiring that the event satisfy both a fixed threshold (either 65 GeV or 70 GeV as shown in the legend) for the cell algorithm and a pufit threshold which varies along the curve. In each plot the background acceptance fractions and the efficiencies are relative to those of the pufit $E_T^{miss} > 110\,$GeV trigger and thus can be greater than one. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger while the cross indicates the performance of the combined (pufit $E_T^{miss}>110\,$GeV and cell $E_T^{miss}>50\,$GeV) trigger.
Relative background acceptance fraction vs. relative efficiency for two different $p_T(\mu\mu)>150\,$GeV threshold for data recorded in the year 2018. Two of the curves show the performance of the stand-alone cell algorithm and the stand-alone pufit algorithm. The other two show combined algorithms each formed by requiring that the event satisfy both a fixed threshold (either 65 GeV or 70 GeV as shown in the legend) for the cell algorithm and a pufit threshold which varies along the curve. In each plot the background acceptance fractions and the efficiencies are relative to those of the pufit $E_T^{miss} > 110\,$GeV trigger and thus can be greater than one. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger while the cross indicates the performance of the combined (pufit $E_T^{miss}>110\,$GeV and cell $E_T^{miss}>50\,$GeV) trigger.
Relative background acceptance fraction vs. relative efficiency for two different $p_T(\mu\mu)>150\,$GeV threshold for data recorded in the year 2018. Two of the curves show the performance of the stand-alone cell algorithm and the stand-alone pufit algorithm. The other two show combined algorithms each formed by requiring that the event satisfy both a fixed threshold (either 65 GeV or 70 GeV as shown in the legend) for the cell algorithm and a pufit threshold which varies along the curve. In each plot the background acceptance fractions and the efficiencies are relative to those of the pufit $E_T^{miss} > 110\,$GeV trigger and thus can be greater than one. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger while the cross indicates the performance of the combined (pufit $E_T^{miss}>110\,$GeV and cell $E_T^{miss}>50\,$GeV) trigger.
Relative background acceptance fraction vs. relative efficiency for two different $p_T(\mu\mu)>150\,$GeV threshold for data recorded in the year 2018. Two of the curves show the performance of the stand-alone cell algorithm and the stand-alone pufit algorithm. The other two show combined algorithms each formed by requiring that the event satisfy both a fixed threshold (either 65 GeV or 70 GeV as shown in the legend) for the cell algorithm and a pufit threshold which varies along the curve. In each plot the background acceptance fractions and the efficiencies are relative to those of the pufit $E_T^{miss} > 110\,$GeV trigger and thus can be greater than one. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger while the cross indicates the performance of the combined (pufit $E_T^{miss}>110\,$GeV and cell $E_T^{miss}>50\,$GeV) trigger.
Relative background acceptance fraction vs. relative efficiency for two different $p_T(\mu\mu)>150\,$GeV threshold for data recorded in the year 2018. Two of the curves show the performance of the stand-alone cell algorithm and the stand-alone pufit algorithm. The other two show combined algorithms each formed by requiring that the event satisfy both a fixed threshold (either 65 GeV or 70 GeV as shown in the legend) for the cell algorithm and a pufit threshold which varies along the curve. In each plot the background acceptance fractions and the efficiencies are relative to those of the pufit $E_T^{miss} > 110\,$GeV trigger and thus can be greater than one. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger while the cross indicates the performance of the combined (pufit $E_T^{miss}>110\,$GeV and cell $E_T^{miss}>50\,$GeV) trigger.
Relative background acceptance fraction vs. relative efficiency for two different $p_T(\mu\mu)>150\,$GeV threshold for data recorded in the year 2018. Two of the curves show the performance of the stand-alone cell algorithm and the stand-alone pufit algorithm. The other two show combined algorithms each formed by requiring that the event satisfy both a fixed threshold (either 65 GeV or 70 GeV as shown in the legend) for the cell algorithm and a pufit threshold which varies along the curve. In each plot the background acceptance fractions and the efficiencies are relative to those of the pufit $E_T^{miss} > 110\,$GeV trigger and thus can be greater than one. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger while the cross indicates the performance of the combined (pufit $E_T^{miss}>110\,$GeV and cell $E_T^{miss}>50\,$GeV) trigger.
Relative background acceptance fraction vs. relative efficiency for two different $p_T(\mu\mu)>150\,$GeV threshold for data recorded in the year 2018. Two of the curves show the performance of the stand-alone cell algorithm and the stand-alone pufit algorithm. The other two show combined algorithms each formed by requiring that the event satisfy both a fixed threshold (either 65 GeV or 70 GeV as shown in the legend) for the cell algorithm and a pufit threshold which varies along the curve. In each plot the background acceptance fractions and the efficiencies are relative to those of the pufit $E_T^{miss} > 110\,$GeV trigger and thus can be greater than one. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger while the cross indicates the performance of the combined (pufit $E_T^{miss}>110\,$GeV and cell $E_T^{miss}>50\,$GeV) trigger.
Relative background acceptance fraction vs. relative efficiency for two different $p_T(\mu\mu)>150\,$GeV threshold for data recorded in the year 2018. Two of the curves show the performance of the stand-alone cell algorithm and the stand-alone pufit algorithm. The other two show combined algorithms each formed by requiring that the event satisfy both a fixed threshold (either 65 GeV or 70 GeV as shown in the legend) for the cell algorithm and a pufit threshold which varies along the curve. In each plot the background acceptance fractions and the efficiencies are relative to those of the pufit $E_T^{miss} > 110\,$GeV trigger and thus can be greater than one. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger while the cross indicates the performance of the combined (pufit $E_T^{miss}>110\,$GeV and cell $E_T^{miss}>50\,$GeV) trigger.
Turn-on efficiency curves are shown for $Z\rightarrow\mu\mu$ events for three algorithms: the cell algorithm alone, the pufit algorithm alone and the combined cell+pufit algorithm. The thresholds are set such that the algorithms have equal rates, and the data were recorded in the year 2018. Here the trigger efficiency is shown with respect to $p_T(\mu\mu)$.
Turn-on efficiency curves are shown for $Z\rightarrow\mu\mu$ events for three algorithms: the cell algorithm alone, the pufit algorithm alone and the combined cell+pufit algorithm. The thresholds are set such that the algorithms have equal rates, and the data were recorded in the year 2018. Here the trigger efficiency is shown with respect to the offline $E_T^{miss}$ calculation with muons treated as being invisible.
Efficiencies for $Z\rightarrow\mu\mu$ events are shown for the L1 $E_T^{miss}>50\,$GeV trigger and for the complete L1+HLT trigger chain that also requires pufit > 110 GeV. Each is shown as a function of $\langle\mu\rangle$ for a $p_T(\mu\mu)$ threshold of 150 GeV.
Efficiencies for $Z\rightarrow\mu\mu$ events are shown for the L1 $E_T^{miss}>50\,$GeV trigger and for the complete L1+HLT trigger chain that also requires pufit > 110 GeV. Each is shown as a function of $\langle\mu\rangle$ for an offline $E_T^{miss}$ threshold of 150 GeV.
Efficiencies for $Z\rightarrow\mu\mu$ events are shown for the L1 $E_T^{miss}>50\,$GeV trigger and for the complete L1+HLT trigger chain that also requires pufit > 110 GeV. Each is shown as a function of $\langle\mu\rangle$ for an $p_T(\mu\mu)$ threshold of 175 GeV.
Efficiencies for $Z\rightarrow\mu\mu$ events are shown for the L1 $E_T^{miss}>50\,$GeV trigger and for the complete L1+HLT trigger chain that also requires pufit > 110 GeV. Each is shown as a function of $\langle\mu\rangle$ for an offline $E_T^{miss}$ threshold of 175 GeV.
HLT_xe70_mht trigger output rate as a function of $\langle\mu\rangle$ shown for an example run in year 2015.
HLT_xe90_mht trigger output rate as a function of $\langle\mu\rangle$ shown for an example run in year 2016.
HLT_xe110_mht trigger output rate as a function of $\langle\mu\rangle$ shown for an example run in year 2016.
HLT_xe110_pufit trigger output rate as a function of $\langle\mu\rangle$ shown for an example run in year 2017. This trigger included an implicit requirement of cell $E_T^{miss}>50\,$GeV.
HLT_xe110_pufit_xe65 trigger output rate as a function of $\langle\mu\rangle$ shown for an example run in year 2018.
HLT_xe110_pufit_xe70 trigger output rate as a function of $\langle\mu\rangle$ shown for an example run in year 2018.
Full-chain trigger efficiencies for each year as a function of $p_T(\mu\mu)$. The efficiency corresponds to that of the lowest unprescaled trigger that is adjusted throughout each year.
Full-chain trigger efficiencies for 2015, 2016, 2017 and 2018 as a function of $\langle\mu\rangle$ for $p_T(\mu\mu)>150$ GeV. The efficiency corresponds to that of the lowest unprescaled trigger that is adjusted throughout the year.
Efficiencies for the first-level trigger L1XE50 and the combined L1+HLT trigger chain HLT_xe110_pufit_xe65_L1XE50 in data recorded in the year 2018 are shown as a function of $\langle\mu\rangle$ for $W\rightarrow e\nu$ and $Z\rightarrow\mu\mu$ selections with offline $E_T^{miss}>150\,$GeV.
Efficiencies for the first-level trigger L1XE50 and the combined L1+HLT trigger chain HLT_xe110_pufit_xe65_L1XE50 in data recorded in the year 2018 are shown as a function of $\langle\mu\rangle$ for $t\bar t$ with offline $E_T^{miss}>150\,$GeV.
Efficiencies for the first-level trigger L1XE50 and the combined L1+HLT trigger chain HLT_xe110_pufit_xe65_L1XE50 in data recorded in the year 2018 are shown as a function of $\langle\mu\rangle$ for $W\rightarrow e\nu$ and $Z\rightarrow\mu\mu$ selections with offline $E_T^{miss}>175\,$GeV.
Efficiencies for the first-level trigger L1XE50 and the combined L1+HLT trigger chain HLT_xe110_pufit_xe65_L1XE50 in data recorded in the year 2018 are shown as a function of $\langle\mu\rangle$ for $t\bar t$ with offline $E_T^{miss}>175\,$GeV.
A search for a heavy neutral Higgs boson, $A$, decaying into a $Z$ boson and another heavy Higgs boson, $H$, is performed using a data sample corresponding to an integrated luminosity of 139 fb$^{-1}$ from proton-proton collisions at $\sqrt{s}$ = 13 TeV recorded by the ATLAS detector at the LHC. The search considers the $Z$ boson decaying into electrons or muons and the $H$ boson into a pair of $b$-quarks or $W$ bosons. The mass range considered is 230-800 GeV for the $A$ boson and 130-700 GeV for the $H$ boson. The data are in good agreement with the background predicted by the Standard Model, and therefore 95% confidence-level upper limits for $\sigma \times B(A\rightarrow ZH) \times B(H\rightarrow bb$ or $H\rightarrow WW)$ are set. The upper limits are in the range 0.0062-0.380 pb for the $H\rightarrow bb$ channel and in the range 0.023-8.9 pb for the $H\rightarrow WW$ channel. An interpretation of the results in the context of two-Higgs-Doublet models is also given.
The mass distribution of the bb system before any mbb window cuts for the 3 tag category in b-associated production. The signal distribution for (mA, mH) = (600, 300) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH)=(600, 300) GeV in the 2 tag category with gluon-gluon fusion production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (600, 300) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH)=(600, 300) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (600, 300) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH)=(670, 500) GeV in the 2 tag category with gluon-gluon fusion production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (670, 500) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (670, 500) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (670, 500) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
Upper bounds at 95% CL on the production cross-section times the branching ratio B(A->ZH)xB(H->bb) in pb for a narrow width A boson produced via gluon-gluon fusion. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected.
Upper bounds at 95% CL on the production cross-section times the branching ratio B(A->ZH)xB(H->bb) in pb for a narrow width A boson produced via b-associated production. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected.
Upper bounds at 95% CL on the total production cross-section (ggA + bbA) times the branching ratio B(A->ZH)xB(H->bb) for an A boson in the 2HDM of type-1 with tan(beta)=1. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used and cos(beta-alpha)=0 is assumed. The excluded contours in the figure correspond to the points of the 2HDM parameter space where the expected and observed limits match the theoretical prediction for the cross-section in the model.
Upper bounds at 95% CL on the total production cross-section (ggA + bbA) times the branching ratio B(A->ZH)xB(H->bb) for an A boson in the 2HDM of type-1 with tan(beta)=5. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used and cos(beta-alpha)=0 is assumed. The excluded contours in the figure correspond to the points of the 2HDM parameter space where the expected and observed limits match the theoretical prediction for the cross-section in the model.
Upper bounds at 95% CL on the total production cross-section (ggA + bbA) times the branching ratio B(A->ZH)xB(H->bb) for an A boson in the 2HDM of type-1 with tan(beta)=10. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used and cos(beta-alpha)=0 is assumed. The excluded contours in the figure correspond to the points of the 2HDM parameter space where the expected and observed limits match the theoretical prediction for the cross-section in the model.
Upper bounds at 95% CL on the total production cross-section (ggA + bbA) times the branching ratio B(A->ZH)xB(H->bb) for an A boson in the 2HDM of type-2 with tan(beta)=1. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used and cos(beta-alpha)=0 is assumed. The excluded contours in the figure correspond to the points of the 2HDM parameter space where the expected and observed limits match the theoretical prediction for the cross-section in the model.
Upper bounds at 95% CL on the total production cross-section (ggA + bbA) times the branching ratio B(A->ZH)xB(H->bb) for an A boson in the 2HDM of type-2 with tan(beta)=5. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used and cos(beta-alpha)=0 is assumed. The excluded contours in the figure correspond to the points of the 2HDM parameter space where the expected and observed limits match the theoretical prediction for the cross-section in the model.
Upper bounds at 95% CL on the total production cross-section (ggA + bbA) times the branching ratio B(A->ZH)xB(H->bb) for an A boson in the 2HDM of type-2 with tan(beta)=10. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used and cos(beta-alpha)=0 is assumed. The excluded contours in the figure correspond to the points of the 2HDM parameter space where the expected and observed limits match the theoretical prediction for the cross-section in the model.
Upper bounds at 95% CL on the total production cross-section (ggA + bbA) times the branching ratio B(A->ZH)xB(H->bb) for an A boson in the 2HDM of type-2 with tan(beta)=20. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used and cos(beta-alpha)=0 is assumed. The excluded contours in the figure correspond to the points of the 2HDM parameter space where the expected and observed limits match the theoretical prediction for the cross-section in the model.
Upper bounds at 95% CL on the total production cross-section (ggA + bbA) times the branching ratio B(A->ZH)xB(H->bb) for an A boson in the lepton specific 2HDM with tan(beta)=1. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used and cos(beta-alpha)=0 is assumed. The excluded contours in the figure correspond to the points of the 2HDM parameter space where the expected and observed limits match the theoretical prediction for the cross-section in the model.
Upper bounds at 95% CL on the total production cross-section (ggA + bbA) times the branching ratio B(A->ZH)xB(H->bb) for an A boson in the lepton specific 2HDM with tan(beta)=2. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used and cos(beta-alpha)=0 is assumed. The excluded contours in the figure correspond to the points of the 2HDM parameter space where the expected and observed limits match the theoretical prediction for the cross-section in the model.
Upper bounds at 95% CL on the total production cross-section (ggA + bbA) times the branching ratio B(A->ZH)xB(H->bb) for an A boson in the lepton specific 2HDM with tan(beta)=3. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used and cos(beta-alpha)=0 is assumed. The excluded contours in the figure correspond to the points of the 2HDM parameter space where the expected and observed limits match the theoretical prediction for the cross-section in the model.
Upper bounds at 95% CL on the total production cross-section (ggA + bbA) times the branching ratio B(A->ZH)xB(H->bb) for an A boson in the flipped 2HDM with tan(beta)=1. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used and cos(beta-alpha)=0 is assumed. The excluded contours in the figure correspond to the points of the 2HDM parameter space where the expected and observed limits match the theoretical prediction for the cross-section in the model.
Upper bounds at 95% CL on the total production cross-section (ggA + bbA) times the branching ratio B(A->ZH)xB(H->bb) for an A boson in the flipped 2HDM with tan(beta)=5. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used and cos(beta-alpha)=0 is assumed. The excluded contours in the figure correspond to the points of the 2HDM parameter space where the expected and observed limits match the theoretical prediction for the cross-section in the model.
Upper bounds at 95% CL on the total production cross-section (ggA + bbA) times the branching ratio B(A->ZH)xB(H->bb) for an A boson in the flipped 2HDM with tan(beta)=10. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used and cos(beta-alpha)=0 is assumed. The excluded contours in the figure correspond to the points of the 2HDM parameter space where the expected and observed limits match the theoretical prediction for the cross-section in the model.
Upper bounds at 95% CL on the total production cross-section (ggA + bbA) times the branching ratio B(A->ZH)xB(H->bb) for an A boson in the flipped 2HDM with tan(beta)=20. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used and cos(beta-alpha)=0 is assumed. The excluded contours in the figure correspond to the points of the 2HDM parameter space where the expected and observed limits match the theoretical prediction for the cross-section in the model.
The mass distribution of the 4q system before any m4q window cuts for gluon-gluon fusion for the llWW channel. The signal distribution for (mA, mH) = (600, 300) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH)=(600, 300) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (600, 300) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH)=(670, 500) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (670, 500) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
Upper bounds at 95% CL on the production cross-section times the branching ratio B(A->ZH)xB(H->WW) in pb for a narrow width A boson produced via gluon-gluon fusion production. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected.
Upper bounds at 95% CL on the production cross-section times the branching ratio B(A->ZH)xB(H->bb) in pb for an A boson with a natural width that is 10% with respect to its mass, produced via gluon-gluon fusion for the llbb final state. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected.
Upper bounds at 95% CL on the production cross-section times the branching ratio B(A->ZH)xB(H->bb) in pb for an A boson with a natural width that is 10% with respect to its mass, via b-associated production for the llbb final state. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected.
Upper bounds at 95% CL on the production cross-section times the branching ratio B(A->ZH)xB(H->bb) in pb for an A boson with a natural width that is 20% with respect to its mass, produced via gluon-gluon fusion for the llbb final state. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected.
Upper bounds at 95% CL on the production cross-section times the branching ratio B(A->ZH)xB(H->bb) in pb for an A boson with a natural width that is 20% with respect to its mass, via b-associated production for the llbb final state. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected.
Upper bounds at 95% CL on the production cross-section times the branching ratio B(A->ZH)xB(H->WW) in pb for an A boson with a natural width that is 10% with respect to its mass, produced via gluon-gluon fusion for the llWW final state. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected.
Upper bounds at 95% CL on the production cross-section times the branching ratio B(A->ZH)xB(H->WW) in pb for an A boson with a natural width that is 20% with respect to its mass, produced via gluon-gluon fusion for the llWW final state. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (440, 130) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (440, 130) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (450, 140) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (450, 140) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (460, 150) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (460, 150) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (460, 160) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (460, 160) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (470, 170) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (470, 170) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (470, 180) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (470, 180) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (420, 190) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (420, 190) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (490, 200) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (490, 200) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (430, 210) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (430, 210) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (440, 220) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (440, 220) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (500, 230) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (500, 230) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (510, 240) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (510, 240) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (520, 250) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (520, 250) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (520, 260) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (520, 260) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (530, 270) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (530, 270) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (540, 280) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (540, 280) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (540, 290) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (540, 290) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (550, 300) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (550, 300) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (550, 310) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (550, 310) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (560, 320) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (560, 320) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (570, 330) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (570, 330) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (570, 340) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (570, 340) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (580, 350) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (580, 350) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (580, 360) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (580, 360) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (590, 370) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (590, 370) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (600, 380) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (600, 380) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (600, 390) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (600, 390) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (610, 400) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (610, 400) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (620, 410) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (620, 410) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (620, 420) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (620, 420) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (630, 430) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (630, 430) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (630, 440) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (630, 440) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (640, 450) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (640, 450) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (650, 460) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (650, 460) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (650, 470) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (650, 470) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (660, 480) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (660, 480) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (670, 490) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (670, 490) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (670, 500) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (670, 500) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (680, 510) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (680, 510) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (680, 520) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (680, 520) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (690, 530) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (690, 530) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (700, 540) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (700, 540) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (700, 550) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (700, 550) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (710, 560) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (710, 560) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (710, 570) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (710, 570) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (720, 580) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (720, 580) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (730, 590) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (730, 590) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (730, 600) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (730, 600) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (740, 610) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (740, 610) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (750, 620) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (750, 620) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (750, 630) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (750, 630) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (760, 640) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (760, 640) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (760, 650) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (760, 650) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (770, 660) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (770, 660) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (780, 670) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (780, 670) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (780, 680) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (780, 680) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (790, 690) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (790, 690) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (440, 130) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (440, 130) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (450, 140) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (450, 140) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (460, 150) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (460, 150) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (460, 160) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (460, 160) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (470, 170) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (470, 170) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (470, 180) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (470, 180) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (420, 190) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (420, 190) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (490, 200) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (490, 200) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (430, 210) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (430, 210) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (440, 220) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (440, 220) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (500, 230) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (500, 230) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (510, 240) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (510, 240) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (520, 250) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (520, 250) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (520, 260) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (520, 260) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (530, 270) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (530, 270) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (540, 280) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (540, 280) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (540, 290) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (540, 290) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (550, 300) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (550, 300) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (550, 310) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (550, 310) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (560, 320) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (560, 320) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (570, 330) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (570, 330) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (570, 340) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (570, 340) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (580, 350) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (580, 350) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (580, 360) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (580, 360) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (590, 370) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (590, 370) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (600, 380) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (600, 380) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (600, 390) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (600, 390) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (610, 400) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (610, 400) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (620, 410) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (620, 410) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (620, 420) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (620, 420) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (630, 430) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (630, 430) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (630, 440) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (630, 440) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (640, 450) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (640, 450) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (720, 580) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (720, 580) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (730, 590) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (730, 590) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (730, 600) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (730, 600) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (740, 610) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (740, 610) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (750, 620) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (750, 620) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (750, 630) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (750, 630) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (760, 640) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (760, 640) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (760, 650) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (760, 650) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (770, 660) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (770, 660) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (780, 670) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (780, 670) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (780, 680) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (780, 680) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (790, 690) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (790, 690) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (400, 200) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (400, 200) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (430, 210) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (430, 210) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (440, 220) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (440, 220) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (500, 230) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (500, 230) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (510, 240) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (510, 240) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (520, 250) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (520, 250) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (520, 260) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (520, 260) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (530, 270) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (530, 270) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (540, 280) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (540, 280) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (540, 290) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (540, 290) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (550, 300) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (550, 300) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (550, 310) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (550, 310) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (560, 320) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (560, 320) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (570, 330) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (570, 330) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (570, 340) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (570, 340) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (580, 350) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (580, 350) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (580, 360) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (580, 360) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
A search is presented for new phenomena in events characterised by high jet multiplicity, no leptons (electrons or muons), and four or more jets originating from the fragmentation of $b$-quarks ($b$-jets). The search uses 139 fb$^{-1}$ of $\sqrt{s}$ = 13 TeV proton-proton collision data collected by the ATLAS experiment at the Large Hadron Collider during Run 2. The dominant Standard Model background originates from multijet production and is estimated using a data-driven technique based on an extrapolation from events with low $b$-jet multiplicity to the high $b$-jet multiplicities used in the search. No significant excess over the Standard Model expectation is observed and 95% confidence-level limits that constrain simplified models of R-parity-violating supersymmetry are determined. The exclusion limits reach 950 GeV in top-squark mass in the models considered.
<b>- - - - - - - - Overview of HEPData Record - - - - - - - -</b> <br><br> <b>Exclusion contours:</b> <ul> <li><a href="?table=stbchionly_obs">Stop to bottom quark and chargino exclusion contour (Obs.)</a> <li><a href="?table=stbchionly_exp">Stop to bottom quark and chargino exclusion contour (Exp.)</a> <li><a href="?table=stbchi_obs">Stop to higgsino LSP exclusion contour (Obs.)</a> <li><a href="?table=stbchi_exp">Stop to higgsino LSP exclusion contour (Exp.)</a> <li><a href="?table=sttN_obs">Stop to top quark and neutralino exclusion contour (Obs.)</a> <li><a href="?table=sttN_exp">Stop to top quark and neutralino exclusion contour (Exp.)</a> </ul> <b>Upper limits:</b> <ul> <li><a href="?table=stbchionly_xSecUL_obs">Obs Xsection upper limit in stop to bottom quark and chargino</a> <li><a href="?table=stop_xSecUL_obs">Obs Xsection upper limit in higgsino LSP</a> <li><a href="?table=stbchionly_xSecUL_exp">Exp Xsection upper limit in stop to bottom quark and chargino</a> <li><a href="?table=stop_xSecUL_exp">Exp Xsection upper limit in higgsino LSP</a> </ul> <b>Kinematic distributions:</b> <ul> <li><a href="?table=SR_yields">SR_yields</a> </ul> <b>Cut flows:</b> <ul> <li><a href="?table=cutflow">cutflow</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>stbchi_6je4be:</b> <a href="?table=stbchi_Acc_6je4be">stbchi_Acc_6je4be</a> <a href="?table=stbchi_Eff_6je4be">stbchi_Eff_6je4be</a> <li> <b>stbchi_7je4be:</b> <a href="?table=stbchi_Acc_7je4be">stbchi_Acc_7je4be</a> <a href="?table=stbchi_Eff_7je4be">stbchi_Eff_7je4be</a> <li> <b>stbchi_8je4be:</b> <a href="?table=stbchi_Acc_8je4be">stbchi_Acc_8je4be</a> <a href="?table=stbchi_Eff_8je4be">stbchi_Eff_8je4be</a> <li> <b>stbchi_9ji4be:</b> <a href="?table=stbchi_Acc_9ji4be">stbchi_Acc_9ji4be</a> <a href="?table=stbchi_Eff_9ji4be">stbchi_Eff_9ji4be</a> <li> <b>stbchi_6je5bi:</b> <a href="?table=stbchi_Acc_6je5bi">stbchi_Acc_6je5bi</a> <a href="?table=stbchi_Eff_6je5bi">stbchi_Eff_6je5bi</a> <li> <b>stbchi_7je5bi:</b> <a href="?table=stbchi_Acc_7je5bi">stbchi_Acc_7je5bi</a> <a href="?table=stbchi_Eff_7je5bi">stbchi_Eff_7je5bi</a> <li> <b>stbchi_8je5bi:</b> <a href="?table=stbchi_Acc_8je5bi">stbchi_Acc_8je5bi</a> <a href="?table=stbchi_Eff_8je5bi">stbchi_Eff_8je5bi</a> <li> <b>stbchi_9ji5bi:</b> <a href="?table=stbchi_Acc_9ji5bi">stbchi_Acc_9ji5bi</a> <a href="?table=stbchi_Eff_9ji5bi">stbchi_Eff_9ji5bi</a> <li> <b>stbchi_8ji5bi:</b> <a href="?table=stbchi_Acc_8ji5bi">stbchi_Acc_8ji5bi</a> <a href="?table=stbchi_Eff_8ji5bi">stbchi_Eff_8ji5bi</a> <li> <b>sttN_6je4be:</b> <a href="?table=sttN_Acc_6je4be">sttN_Acc_6je4be</a> <a href="?table=sttN_Eff_6je4be">sttN_Eff_6je4be</a> <li> <b>sttN_7je4be:</b> <a href="?table=sttN_Acc_7je4be">sttN_Acc_7je4be</a> <a href="?table=sttN_Eff_7je4be">sttN_Eff_7je4be</a> <li> <b>sttN_8je4be:</b> <a href="?table=sttN_Acc_8je4be">sttN_Acc_8je4be</a> <a href="?table=sttN_Eff_8je4be">sttN_Eff_8je4be</a> <li> <b>sttN_9ji4be:</b> <a href="?table=sttN_Acc_9ji4be">sttN_Acc_9ji4be</a> <a href="?table=sttN_Eff_9ji4be">sttN_Eff_9ji4be</a> <li> <b>sttN_6je5bi:</b> <a href="?table=sttN_Acc_6je5bi">sttN_Acc_6je5bi</a> <a href="?table=sttN_Eff_6je5bi">sttN_Eff_6je5bi</a> <li> <b>sttN_7je5bi:</b> <a href="?table=sttN_Acc_7je5bi">sttN_Acc_7je5bi</a> <a href="?table=sttN_Eff_7je5bi">sttN_Eff_7je5bi</a> <li> <b>sttN_8je5bi:</b> <a href="?table=sttN_Acc_8je5bi">sttN_Acc_8je5bi</a> <a href="?table=sttN_Eff_8je5bi">sttN_Eff_8je5bi</a> <li> <b>sttN_9ji5bi:</b> <a href="?table=sttN_Acc_9ji5bi">sttN_Acc_9ji5bi</a> <a href="?table=sttN_Eff_9ji5bi">sttN_Eff_9ji5bi</a> <li> <b>sttN_8ji5bi:</b> <a href="?table=sttN_Acc_8ji5bi">sttN_Acc_8ji5bi</a> <a href="?table=sttN_Eff_8ji5bi">sttN_Eff_8ji5bi</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 $\it{m}_{\tilde{\chi}^{\pm}_{1}}$ vs. $\it{m}_{\tilde{t}}$. Masses that are within the contours are excluded. Limits are shown for $B(\tilde{t} \rightarrow b \chi^{+}_{1})$ equal to unity.
The expected exclusion contour at 95% CL as a function of the $\it{m}_{\tilde{\chi}^{\pm}_{1}}$ vs. $\it{m}_{\tilde{t}}$. Masses that are within the contour are excluded. Limits are shown for $B(\tilde{t} \rightarrow b \chi^{+}_{1})$ equal to unity.
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. Limits are shown in the case of a higgsino LSP. The results are constrained by the kinematic limits of the top-squark decay into a chargino and a bottom quark (upper diagonal line) and into a neutralino and a top quark (lower diagonal line), respectively.
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 contours are excluded. Limits are shown in the case of a higgsino LSP. The results are constrained by the kinematic limits of the top-squark decay into a chargino and a bottom quark (upper diagonal line) and into a neutralino and a top quark (lower diagonal line), respectively.
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. Limits are shown for the region $m_{\tilde{t}} - m_{\tilde{\chi}^0_{1,2}, \tilde{\chi}^\pm_{1}} \geq m_\text{top}$ where $B(\tilde{t} \rightarrow b \chi^{+}_{1}) = B(\tilde{t} \rightarrow t \chi^{0}_{1,2}) = 0.5$.
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 contours are excluded. Limits are shown for the region $m_{\tilde{t}} - m_{\tilde{\chi}^0_{1,2}, \tilde{\chi}^\pm_{1}} \geq m_\text{top}$ where $B(\tilde{t} \rightarrow b \chi^{+}_{1}) = B(\tilde{t} \rightarrow t \chi^{0}_{1,2}) = 0.5$.
Observed model-dependent upper limit on the cross section for the $(\tilde{t},\tilde{\chi}^{\pm}_{1})$ signal grid. Limits are shown for $B(\tilde{t} \rightarrow b \chi^{+}_{1})$ equal to unity.
Observed model-dependent upper limit on the cross section for the $(\tilde{t},\tilde{\chi}^{\pm}_{1} / \tilde{\chi}^{0}_{1,2})$ signal grid. Limits are shown in the case of a higgsino LSP. The results are constrained by the kinematic limits of the top-squark decay into a chargino and a bottom quark (upper diagonal line) and into a neutralino and a top quark (lower diagonal line), respectively.
Expected model-dependent upper limit on the cross section for the $(\tilde{t},\tilde{\chi}^{\pm}_{1})$ signal grid. Limits are shown for $B(\tilde{t} \rightarrow b \chi^{+}_{1})$ equal to unity.
Expected model-dependent upper limit on the cross section for the $(\tilde{t},\tilde{\chi}^{\pm}_{1} / \tilde{\chi}^{0}_{1,2})$ signal grid. Limits are shown in the case of a higgsino LSP. The results are constrained by the kinematic limits of the top-squark decay into a chargino and a bottom quark (upper diagonal line) and into a neutralino and a top quark (lower diagonal line), respectively.
Expected background and observed number of events in different jet and $b$-tag multiplicity bins.
Cut flow for a model of top-squark pair production with the top squark decaying to a $b$-quark and a chargino. The chargino decays through the non-zero RPV coupling $\lambda^{''}_{323}$ via a virtual top squark to $bbs$ quark triplets ($m_{\tilde{t}}$ = 800 GeV, $m_{\tilde{\chi}^{\pm}_{1}}$ = 750 GeV). The multijet trigger consists of four jets satisfying $p_{\text{T}}\geq(100)120$ GeV for the 2015-2016 (2017-2018) data period. Selections with negligible inefficiencies on the given sample, such as data quality requirements, are not displayed. The numbers in $N_{\text{weighted}}$ are normalized by the integrated luminosity of 139 fb$^{-1}$.
Signal acceptance for $\tilde{t} \rightarrow b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.
Signal acceptance for $\tilde{t} \rightarrow b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.
Signal acceptance for $\tilde{t} \rightarrow b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.
Signal acceptance for $\tilde{t} \rightarrow b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.
Signal acceptance for $\tilde{t} \rightarrow b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.
Signal acceptance for $\tilde{t} \rightarrow b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.
Signal acceptance for $\tilde{t} \rightarrow b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.
Signal acceptance for $\tilde{t} \rightarrow b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.
Signal acceptance for $\tilde{t} \rightarrow b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.
Signal efficiency for $\tilde{t} \rightarrow b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the efficiency given in the table is reported in %.
Signal efficiency for $\tilde{t} \rightarrow b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the efficiency given in the table is reported in %.
Signal efficiency for $\tilde{t} \rightarrow b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the efficiency given in the table is reported in %.
Signal efficiency for $\tilde{t} \rightarrow b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the efficiency given in the table is reported in %.
Signal efficiency for $\tilde{t} \rightarrow b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the efficiency given in the table is reported in %.
Signal efficiency for $\tilde{t} \rightarrow b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the efficiency given in the table is reported in %.
Signal efficiency for $\tilde{t} \rightarrow b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the efficiency given in the table is reported in %.
Signal efficiency for $\tilde{t} \rightarrow b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the efficiency given in the table is reported in %.
Signal efficiency for $\tilde{t} \rightarrow b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the efficiency given in the table is reported in %.
Signal acceptance for $\tilde{t} \rightarrow t\tilde{\chi}^{0}_{1,2}(\tilde{\chi}^{0}_{1,2} \rightarrow tbs) / b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.
Signal acceptance for $\tilde{t} \rightarrow t\tilde{\chi}^{0}_{1,2}(\tilde{\chi}^{0}_{1,2} \rightarrow tbs) / b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.
Signal acceptance for $\tilde{t} \rightarrow t\tilde{\chi}^{0}_{1,2}(\tilde{\chi}^{0}_{1,2} \rightarrow tbs) / b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.
Signal acceptance for $\tilde{t} \rightarrow t\tilde{\chi}^{0}_{1,2}(\tilde{\chi}^{0}_{1,2} \rightarrow tbs) / b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.
Signal acceptance for $\tilde{t} \rightarrow t\tilde{\chi}^{0}_{1,2}(\tilde{\chi}^{0}_{1,2} \rightarrow tbs) / b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.
Signal acceptance for $\tilde{t} \rightarrow t\tilde{\chi}^{0}_{1,2}(\tilde{\chi}^{0}_{1,2} \rightarrow tbs) / b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.
Signal acceptance for $\tilde{t} \rightarrow t\tilde{\chi}^{0}_{1,2}(\tilde{\chi}^{0}_{1,2} \rightarrow tbs) / b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.
Signal acceptance for $\tilde{t} \rightarrow t\tilde{\chi}^{0}_{1,2}(\tilde{\chi}^{0}_{1,2} \rightarrow tbs) / b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.
Signal acceptance for $\tilde{t} \rightarrow t\tilde{\chi}^{0}_{1,2}(\tilde{\chi}^{0}_{1,2} \rightarrow tbs) / b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.
Signal acceptance for $\tilde{t} \rightarrow t\tilde{\chi}^{0}_{1,2}(\tilde{\chi}^{0}_{1,2} \rightarrow tbs) / b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.
Signal acceptance for $\tilde{t} \rightarrow t\tilde{\chi}^{0}_{1,2}(\tilde{\chi}^{0}_{1,2} \rightarrow tbs) / b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.
Signal acceptance for $\tilde{t} \rightarrow t\tilde{\chi}^{0}_{1,2}(\tilde{\chi}^{0}_{1,2} \rightarrow tbs) / b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.
Signal acceptance for $\tilde{t} \rightarrow t\tilde{\chi}^{0}_{1,2}(\tilde{\chi}^{0}_{1,2} \rightarrow tbs) / b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.
Signal acceptance for $\tilde{t} \rightarrow t\tilde{\chi}^{0}_{1,2}(\tilde{\chi}^{0}_{1,2} \rightarrow tbs) / b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.
Signal acceptance for $\tilde{t} \rightarrow t\tilde{\chi}^{0}_{1,2}(\tilde{\chi}^{0}_{1,2} \rightarrow tbs) / b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.
Signal acceptance for $\tilde{t} \rightarrow t\tilde{\chi}^{0}_{1,2}(\tilde{\chi}^{0}_{1,2} \rightarrow tbs) / b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.
Signal acceptance for $\tilde{t} \rightarrow t\tilde{\chi}^{0}_{1,2}(\tilde{\chi}^{0}_{1,2} \rightarrow tbs) / b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.
Signal acceptance for $\tilde{t} \rightarrow t\tilde{\chi}^{0}_{1,2}(\tilde{\chi}^{0}_{1,2} \rightarrow tbs) / b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.
A search for the pair production of heavy leptons as predicted by the type-III seesaw mechanism is presented. The search uses proton-proton collision data at a centre-of-mass energy of 13 TeV, corresponding to 139 fb$^{-1}$ of integrated luminosity recorded by the ATLAS detector during Run 2 of the Large Hadron Collider. The analysis focuses on the final state with two light leptons (electrons or muons) of different flavour and charge combinations, with at least two jets and large missing transverse momentum. No significant excess over the Standard Model expectation is observed. The results are translated into exclusion limits on heavy-lepton masses, and the observed lower limit on the mass of the type-III seesaw heavy leptons is 790 GeV at 95% confidence level.
Cross-sections of the type-III seesaw process for mass points used in the analysis. Branching ratios into at least two leptons are presented with the corresponding effective cross-section.
Expected and observed 95 % CLs exclusion limits for the type-III seesaw process with the corresponding one- and two-standard-deviation bands, showing the 95 % CL upper limit on the cross-section.
Selection efficiencies in percentage relative to the events with at least two leptons for signal mass points used in the analysis. The efficiency is defined as the ratio of expected signal events in a signal region compared with the number of expected events produced, for integrated luminosity 139 fb$^{-1}$.
Expected signal yields after each of the analysis selection cuts for the 800 GeV mass point. Total expected events represents all type-III seesaw events expected for integrated luminosity 139 fb$^{-1}$. Only events with at least two leptons were generated for this analysis.
Distribution of $H_\text{T} + E_\text{T}^\text{miss}$ in the opposite-sign electron-electron signal region after the background-only fit.
Distribution of $H_\text{T} + E_\text{T}^\text{miss}$ in the opposite-sign electron-muon signal region after the background-only fit.
Distribution of $H_\text{T} + E_\text{T}^\text{miss}$ in the opposite-sign muon-muon signal region after the background-only fit.
Distribution of $H_\text{T} + E_\text{T}^\text{miss}$ in the same-sign electron-electron signal region after the background-only fit.
Distribution of $H_\text{T} + E_\text{T}^\text{miss}$ in the same-sign electron-muon signal region after the background-only fit.
Distribution of $H_\text{T} + E_\text{T}^\text{miss}$ in the same-sign muon-muon signal region after the background-only fit.
This paper presents a search for new heavy particles decaying into a pair of top quarks using 139 fb$^{-1}$ of proton--proton collision data recorded at a centre-of-mass energy of $\sqrt{s}=13$ TeV with the ATLAS detector at the Large Hadron Collider. The search is performed using events consistent with pair production of high-transverse-momentum top quarks and their subsequent decays into the fully hadronic final states. The analysis is optimized for resonances decaying into a $t\bar{t}$ pair with mass above 1.4 TeV, exploiting a dedicated multivariate technique with jet substructure to identify hadronically decaying top quarks using large-radius jets and evaluating the background expectation from data. No significant deviation from the background prediction is observed. Limits are set on the production cross-section times branching fraction for the new $Z'$ boson in a topcolor-assisted-technicolor model. The $Z'$ boson masses below 3.9 and 4.7 TeV are excluded at 95% confidence level for the decay widths of 1% and 3%, respectively.
Acceptance and acceptance times selection efficiency as a function of $m^{gen}_{t\bar{t}}$ in SR$1b$. The acceptance is measured as the fraction of events with two leading truth-contained large-$R$ jets, both satisfying the kinematic requirements, but not containing generator-level electrons or muons, as described in the paper. The acceptance $\times$ efficiency is calculated with respect to the full analysis selections including top- and $b$-tagging requirements on the two leading large-$R$ jets. The $m^{gen}_{t\bar{t}}$ is calculated from the momenta of top and anti-top quarks at the generator level before final-state radiation. The branching fractions of the $t \bar{t}$ into all possible final states are included in the acceptance calculation.
Acceptance and acceptance times selection efficiency as a function of $m^{gen}_{t\bar{t}}$ in SR$2b$. The acceptance is measured as the fraction of events with two leading truth-contained large-$R$ jets, both satisfying the kinematic requirements, but not containing generator-level electrons or muons, as described in the paper. The acceptance $\times$ efficiency is calculated with respect to the full analysis selections including top- and $b$-tagging requirements on the two leading large-$R$ jets. The $m^{gen}_{t\bar{t}}$ is calculated from the momenta of top and anti-top quarks at the generator level before final-state radiation. The branching fractions of the $t \bar{t}$ into all possible final states are included in the acceptance calculation.
Observed $m_{t\bar{t}}^{reco}$ distributions in data for SR$1b$, shown together with the result of the fit with the three-shape-parameter function. The error bars indicate the effect of the fit parameter uncertainty on the background prediction. The bin width of the distributions is chosen to be the same as that used in the background parameterization.
Observed $m_{t\bar{t}}^{reco}$ distributions in data for SR$2b$, shown together with the result of the fit with the three-shape-parameter function. The error bars indicate the effect of the fit parameter uncertainty on the background prediction. The bin width of the distributions is chosen to be the same as that used in the background parameterization.
Observed and expected upper limits on the cross-section times branching fraction of the $Z'_{TC2} \rightarrow t\bar{t}$ as a function of the $Z'_{TC2}$ mass ($\Gamma/m = 1.2$%).
Fit parameter values obtained from fits to data in the two signal regions. The fit function is $f(x) = p_{0} (1-x)^{p_{1}} x^{p_{2} + p_{3} \log(x)}$, where $x = m^{reco}_{t\bar{t}}/\sqrt{s}$.
The associated production of a Higgs boson with a $W$ or $Z$ boson decaying into leptons and where the Higgs boson decays to a $b\bar{b}$ pair is measured in the high vector-boson transverse momentum regime, above 250 GeV, with the ATLAS detector. The analysed data, corresponding to an integrated luminosity of 139 fb$^{-1}$, were collected in proton-proton collisions at the Large Hadron Collider between 2015 and 2018 at a centre-of-mass energy of $\sqrt{s} = 13$ TeV. The measured signal strength, defined as the ratio of the measured signal yield to that predicted by the Standard Model, is $0.72 ^{+0.39}_{-0.36}$ corresponding to an observed (expected) significance of 2.1 (2.7) standard deviations. Cross-sections of associated production of a Higgs boson decaying into $b$ quark pairs with a $W$ or $Z$ gauge boson, decaying into leptons, are measured in two exclusive vector boson transverse momentum regions, 250-400 GeV and above 400 GeV, and interpreted as constraints on anomalous couplings in the framework of a Standard Model effective field theory.
Observed correlations between the measured reduced stage-1.2 simplified template VH, V->leptons and H->bb cross sections, including both the statistical and systematic uncertainties.
Measured and predicted VH, V->leptons reduced stage-1.2 simplified template cross sections times the H->bb and V->leptons branching fractions with corresponding uncertainties. All possible Z decays into neutral and charged leptons are considered.
Linear combinations of Wilson coefficients corresponding to the principal component decomposition eigenvectors. The corresponding eigenvalues, representing in the gaussian approximation the inverse uncertainty square of the measured eigenvector, is also indicated.
This paper presents results of searches for electroweak production of supersymmetric particles in models with compressed mass spectra. The searches use 139 fb$^{-1}$ of $\sqrt{s}=13$ TeV proton-proton collision data collected by the ATLAS experiment at the Large Hadron Collider. Events with missing transverse momentum and two same-flavor, oppositely charged, low transverse momentum leptons are selected, and are further categorized by the presence of hadronic activity from initial-state radiation or a topology compatible with vector-boson fusion processes. The data are found to be consistent with predictions from the Standard Model. The results are interpreted using simplified models of $R$-parity-conserving supersymmetry in which the lightest supersymmetric partner is a neutralino with a mass similar to the lightest chargino, the second-to-lightest neutralino or the slepton. Lower limits on the masses of charginos in different simplified models range from 193 GeV to 240 GeV for moderate mass splittings, and extend down to mass splittings of 1.5 GeV to 2.4 GeV at the LEP chargino bounds (92.4 GeV). Similar lower limits on degenerate light-flavor sleptons extend up to masses of 251 GeV and down to mass splittings of 550 MeV. Constraints on vector-boson fusion production of electroweak SUSY states are also presented.
Expected 95% CL exclusion sensitivity for simplified models of direct higgsino production.
Expected 95% CL exclusion sensitivity for simplified models of direct higgsino production.
Expected 95% CL exclusion sensitivity for simplified models of direct higgsino production.
Expected 95% CL exclusion sensitivity for simplified models of direct higgsino production.
Observed 95% CL exclusion sensitivity for simplified models of direct higgsino production.
Observed 95% CL exclusion sensitivity for simplified models of direct higgsino production.
Observed 95% CL exclusion sensitivity for simplified models of direct higgsino production.
Observed 95% CL exclusion sensitivity for simplified models of direct higgsino production.
Expected 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})<0$.
Expected 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})<0$.
Expected 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})<0$.
Expected 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})<0$.
Observed 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})<0$.
Observed 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})<0$.
Observed 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})<0$.
Observed 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})<0$.
Expected 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})>0$.
Expected 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})>0$.
Expected 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})>0$.
Expected 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})>0$.
Observed 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})>0$.
Observed 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})>0$.
Observed 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})>0$.
Observed 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})>0$.
Expected 95% CL exclusion sensitivity for simplified models of VBF wino-bino production.
Expected 95% CL exclusion sensitivity for simplified models of VBF wino-bino production.
Expected 95% CL exclusion sensitivity for simplified models of VBF wino-bino production.
Expected 95% CL exclusion sensitivity for simplified models of VBF wino-bino production.
Observed 95% CL exclusion sensitivity for simplified models of direct wino-bino production.
Observed 95% CL exclusion sensitivity for simplified models of direct wino-bino production.
Observed 95% CL exclusion sensitivity for simplified models of direct wino-bino production.
Observed 95% CL exclusion sensitivity for simplified models of direct wino-bino production.
Expected 95% CL exclusion sensitivity for simplified models of direct slepton production.
Expected 95% CL exclusion sensitivity for simplified models of direct slepton production.
Expected 95% CL exclusion sensitivity for simplified models of direct slepton production.
Expected 95% CL exclusion sensitivity for simplified models of direct slepton production.
Observed 95% CL exclusion sensitivity for simplified models of direct slepton production.
Observed 95% CL exclusion sensitivity for simplified models of direct slepton production.
Observed 95% CL exclusion sensitivity for simplified models of direct slepton production.
Observed 95% CL exclusion sensitivity for simplified models of direct slepton production.
Expected 95% CL exclusion sensitivity for simplified models of direct LH smuon production.
Expected 95% CL exclusion sensitivity for simplified models of direct LH smuon production.
Expected 95% CL exclusion sensitivity for simplified models of direct smuon production.
Expected 95% CL exclusion sensitivity for simplified models of direct smuon production.
Observed 95% CL exclusion sensitivity for simplified models of direct LH smuon production.
Observed 95% CL exclusion sensitivity for simplified models of direct LH smuon production.
Observed 95% CL exclusion sensitivity for simplified models of direct smuon production.
Observed 95% CL exclusion sensitivity for simplified models of direct smuon production.
Expected 95% CL exclusion sensitivity for simplified models of direct RH smuon production.
Expected 95% CL exclusion sensitivity for simplified models of direct RH smuon production.
Expected 95% CL exclusion sensitivity for simplified models of direct selectron production.
Expected 95% CL exclusion sensitivity for simplified models of direct selectron production.
Observed 95% CL exclusion sensitivity for simplified models of direct RH smuon production.
Observed 95% CL exclusion sensitivity for simplified models of direct RH smuon production.
Observed 95% CL exclusion sensitivity for simplified models of direct selectron production.
Observed 95% CL exclusion sensitivity for simplified models of direct selectron production.
Expected 95% CL exclusion sensitivity for simplified models of direct LH selectron production.
Expected 95% CL exclusion sensitivity for simplified models of direct LH selectron production.
Expected 95% CL exclusion sensitivity for simplified models of direct LH slepton production.
Expected 95% CL exclusion sensitivity for simplified models of direct LH slepton production.
Observed 95% CL exclusion sensitivity for simplified models of direct LH selectron production.
Observed 95% CL exclusion sensitivity for simplified models of direct LH selectron production.
Observed 95% CL exclusion sensitivity for simplified models of direct LH slepton production.
Observed 95% CL exclusion sensitivity for simplified models of direct LH slepton production.
Expected 95% CL exclusion sensitivity for simplified models of direct RH selectron production.
Expected 95% CL exclusion sensitivity for simplified models of direct RH selectron production.
Expected 95% CL exclusion sensitivity for simplified models of direct RH slepton production.
Expected 95% CL exclusion sensitivity for simplified models of direct RH slepton production.
Observed 95% CL exclusion sensitivity for simplified models of direct RH selectron production.
Observed 95% CL exclusion sensitivity for simplified models of direct RH selectron production.
Observed 95% CL exclusion sensitivity for simplified models of direct RH slepton production.
Observed 95% CL exclusion sensitivity for simplified models of direct RH slepton production.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Expected 95% CL exclusion sensitivity for simplified models of direct LH smuon production.
Expected 95% CL exclusion sensitivity for simplified models of direct LH smuon production.
Efficiency for the C1C1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the C1C1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Observed 95% CL exclusion sensitivity for simplified models of direct LH smuon production.
Observed 95% CL exclusion sensitivity for simplified models of direct LH smuon production.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Expected 95% CL exclusion sensitivity for simplified models of direct RH smuon production.
Expected 95% CL exclusion sensitivity for simplified models of direct RH smuon production.
Efficiency for the C1C1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the C1C1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Observed 95% CL exclusion sensitivity for simplified models of direct RH smuon production.
Observed 95% CL exclusion sensitivity for simplified models of direct RH smuon production.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Expected 95% CL exclusion sensitivity for simplified models of direct LH selectron production.
Expected 95% CL exclusion sensitivity for simplified models of direct LH selectron production.
Efficiency for the C1C1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the C1C1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Observed 95% CL exclusion sensitivity for simplified models of direct LH selectron production.
Observed 95% CL exclusion sensitivity for simplified models of direct LH selectron production.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Expected 95% CL exclusion sensitivity for simplified models of direct RH selectron production.
Expected 95% CL exclusion sensitivity for simplified models of direct RH selectron production.
Efficiency for the N2N1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Observed 95% CL exclusion sensitivity for simplified models of direct RH selectron production.
Observed 95% CL exclusion sensitivity for simplified models of direct RH selectron production.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the C1C1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the C1C1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the C1C1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the C1C1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the C1C1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the C1C1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-3}$) for the slepton process in the SR-S region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Acceptance (note the $z$-axis is in units of $10^{-3}$) for the slepton process in the SR-S region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the slepton process in the SR-S region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Efficiency for the slepton process in the SR-S region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-3}$) for the slepton process in the SR-S-high region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Acceptance (note the $z$-axis is in units of $10^{-3}$) for the slepton process in the SR-S-high region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the slepton process in the SR-S-high region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Efficiency for the slepton process in the SR-S-high region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-3}$) for the slepton process in the SR-S-low region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Acceptance (note the $z$-axis is in units of $10^{-3}$) for the slepton process in the SR-S-low region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the slepton process in the SR-S-low region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Efficiency for the slepton process in the SR-S-low region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the C1C1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the C1C1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-3}$) for the slepton process in the SR-S region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Acceptance (note the $z$-axis is in units of $10^{-3}$) for the slepton process in the SR-S region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Efficiency for the C1C1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the C1C1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the slepton process in the SR-S region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Efficiency for the slepton process in the SR-S region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-3}$) for the slepton process in the SR-S-high region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Acceptance (note the $z$-axis is in units of $10^{-3}$) for the slepton process in the SR-S-high region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Efficiency for the C1C1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the C1C1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the slepton process in the SR-S-high region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Efficiency for the slepton process in the SR-S-high region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-3}$) for the slepton process in the SR-S-low region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Acceptance (note the $z$-axis is in units of $10^{-3}$) for the slepton process in the SR-S-low region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Efficiency for the N2N1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2N1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the slepton process in the SR-S-low region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Efficiency for the slepton process in the SR-S-low region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2N1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2N1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the C1C1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the C1C1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2N1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2N1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the C1C1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the C1C1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1p VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1p VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the C1C1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the C1C1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1p VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1p VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2N1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2N1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1p VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1p VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2N1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2N1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1m VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1m VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2N1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2N1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1m VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1m VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1p VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1p VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1m VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1m VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1p VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1p VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Observed and Expected upper cross-section limits for wino-bino scenarios, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})>0$.
Observed and Expected upper cross-section limits for wino-bino scenarios, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})>0$.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Observed and Expected upper cross-section limits for wino-bino scenarios, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})<0$.
Observed and Expected upper cross-section limits for wino-bino scenarios, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})<0$.
Efficiency for the N2C1p VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1p VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Observed and Expected upper cross-section limits for higgsino scenarios.
Observed and Expected upper cross-section limits for higgsino scenarios.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Observed and Expected upper cross-section limits for higgsino scenarios, assuming VBF production..
Observed and Expected upper cross-section limits for higgsino scenarios, assuming VBF production..
Efficiency for the N2C1m VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1m VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Observed and Expected upper cross-section limits for direct slepton scenarios.
Observed and Expected upper cross-section limits for direct slepton scenarios.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Observed and Expected upper cross-section limits for direct LH slepton scenarios.
Observed and Expected upper cross-section limits for direct LH slepton scenarios.
Efficiency for the N2C1m VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1m VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Observed and Expected upper cross-section limits for direct RH slepton scenarios.
Observed and Expected upper cross-section limits for direct RH slepton scenarios.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Observed and Expected upper cross-section limits for direct smuon scenarios.
Observed and Expected upper cross-section limits for direct smuon scenarios.
Efficiency for the N2C1m VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1m VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Observed and Expected upper cross-section limits for direct LH smuon scenarios.
Observed and Expected upper cross-section limits for direct LH smuon scenarios.
Observed and Expected upper cross-section limits for wino-bino scenarios, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})>0$.
Observed and Expected upper cross-section limits for wino-bino scenarios, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})>0$.
Observed and Expected upper cross-section limits for direct RH smuon scenarios.
Observed and Expected upper cross-section limits for direct RH smuon scenarios.
Observed and Expected upper cross-section limits for wino-bino scenarios, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})<0$.
Observed and Expected upper cross-section limits for wino-bino scenarios, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})<0$.
Observed and Expected upper cross-section limits for direct selectron scenarios.
Observed and Expected upper cross-section limits for direct selectron scenarios.
Observed and Expected upper cross-section limits for higgsino scenarios.
Observed and Expected upper cross-section limits for higgsino scenarios.
Observed and Expected upper cross-section limits for direct LH selectron scenarios.
Observed and Expected upper cross-section limits for direct LH selectron scenarios.
Observed and Expected upper cross-section limits for higgsino scenarios, assuming VBF production..
Observed and Expected upper cross-section limits for higgsino scenarios, assuming VBF production..
Observed and Expected upper cross-section limits for direct RH selectron scenarios.
Observed and Expected upper cross-section limits for direct RH selectron scenarios.
Observed and Expected upper cross-section limits for direct slepton scenarios.
Observed and Expected upper cross-section limits for direct slepton scenarios.
Number of signal events in SR-E-1L1T for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-E-1L1T for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Observed and Expected upper cross-section limits for direct LH slepton scenarios.
Observed and Expected upper cross-section limits for direct LH slepton scenarios.
Number of signal events in SR-E-high for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-E-high for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Observed and Expected upper cross-section limits for direct RH slepton scenarios.
Observed and Expected upper cross-section limits for direct RH slepton scenarios.
Number of signal events in SR-E-low for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-E-low for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Observed and Expected upper cross-section limits for direct smuon scenarios.
Observed and Expected upper cross-section limits for direct smuon scenarios.
Number of signal events in SR-E-med for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-E-med for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Observed and Expected upper cross-section limits for direct LH smuon scenarios.
Observed and Expected upper cross-section limits for direct LH smuon scenarios.
Number of signal events in SR-S-high for the (m($\tilde{\ell}$),m($\tilde{\chi}_{1}^{0}$)) = (150 GeV, 140 GeV) Slepton signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-S-high for the (m($\tilde{\ell}$),m($\tilde{\chi}_{1}^{0}$)) = (150 GeV, 140 GeV) Slepton signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Observed and Expected upper cross-section limits for direct RH smuon scenarios.
Observed and Expected upper cross-section limits for direct RH smuon scenarios.
Number of signal events in SR-S-low for the (m($\tilde{\ell}$),m($\tilde{\chi}_{1}^{0}$)) = (150 GeV, 140 GeV) Slepton signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-S-low for the (m($\tilde{\ell}$),m($\tilde{\chi}_{1}^{0}$)) = (150 GeV, 140 GeV) Slepton signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Observed and Expected upper cross-section limits for direct selectron scenarios.
Observed and Expected upper cross-section limits for direct selectron scenarios.
Number of signal events in SR-VBF for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (100 GeV, 95 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-VBF for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (100 GeV, 95 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Observed and Expected upper cross-section limits for direct LH selectron scenarios.
Observed and Expected upper cross-section limits for direct LH selectron scenarios.
Observed and Expected upper cross-section limits for direct RH selectron scenarios.
Observed and Expected upper cross-section limits for direct RH selectron scenarios.
Number of signal events in SR-E-1L1T for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-E-1L1T for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-E-high for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-E-high for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-E-low for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-E-low for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-E-med for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-E-med for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-S-high for the (m($\tilde{\ell}$),m($\tilde{\chi}_{1}^{0}$)) = (150 GeV, 140 GeV) Slepton signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-S-high for the (m($\tilde{\ell}$),m($\tilde{\chi}_{1}^{0}$)) = (150 GeV, 140 GeV) Slepton signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-S-low for the (m($\tilde{\ell}$),m($\tilde{\chi}_{1}^{0}$)) = (150 GeV, 140 GeV) Slepton signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-S-low for the (m($\tilde{\ell}$),m($\tilde{\chi}_{1}^{0}$)) = (150 GeV, 140 GeV) Slepton signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-VBF for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (100 GeV, 95 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-VBF for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (100 GeV, 95 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
A search for charged leptons with large impact parameters using 139 fb$^{-1}$ of $\sqrt{s} = 13$ TeV $pp$ collision data from the ATLAS detector at the LHC is presented, addressing a long-standing gap in coverage of possible new physics signatures. Results are consistent with the background prediction. This search provides unique sensitivity to long-lived scalar supersymmetric lepton-partners (sleptons). For lifetimes of 0.1 ns, selectron, smuon and stau masses up to 720 GeV, 680 GeV, and 340 GeV are respectively excluded at 95% confidence level, drastically improving on the previous best limits from LEP.
Cutflow for SR-$ee$ for 5 representative signal points. For the following $\tilde{e}$ mass and lifetime points, the number of Monte Carlo events generated are: 24,000 for (100 GeV, 0.01 ns), 16,000 for (300 GeV, 1 ns), and 12,000 for (500 GeV, 0.1 ns). For the $\tilde{\tau}$ mass and lifetime points, the number of Monte Carlo events generated are: 30,000 for (200 GeV, 0.1 ns), and 104,000 for (300 GeV, 0.1 ns).
Cutflow for SR-$e\mu$ for 2 representative signal points. For the $\tilde{\tau}$ mass and lifetime points, the number of Monte Carlo events generated are: 30,000 for (200 GeV, 0.1 ns), and 104,000 for (300 GeV, 0.1 ns).
Cutflow for SR-$\mu\mu$ for 5 representative signal points. For the following $\tilde{\mu}$ mass and lifetime points, the number of Monte Carlo events generated are: 24,000 for (100 GeV, 0.01 ns), 16,000 for (300 GeV, 1 ns), and 12,000 for (500 GeV, 0.1 ns). For the $\tilde{\tau}$ mass and lifetime points, the number of Monte Carlo events generated are: 30,000 for (200 GeV, 0.1 ns), and 104,000 for (300 GeV, 0.1 ns).
Upper limits on observed signal cross section, $\sigma_\text{obs}^\text{95}$, where all slepton flavors are mass degenerate (co-NLSP).
Upper limits on observed signal cross section, $\sigma_\text{obs}^\text{95}$, for the selectron signal model. Selectron ($\tilde{e}_{L, R}$) refers to the scalar superpartners of left- and right-handed electrons.
Upper limits on observed signal cross section, $\sigma_\text{obs}^\text{95}$, for the superpartners of the left-handed electrons, $\tilde{e}_L$.
Upper limits on observed signal cross section, $\sigma_\text{obs}^\text{95}$, for the superpartners of the right-handed electrons, $\tilde{e}_R$.
Upper limits on observed signal cross section, $\sigma_\text{obs}^\text{95}$, for the smuon signal model. Smuon ($\tilde{\mu}_{L, R}$) refers to the scalar superpartners of left- and right-handed muons.
Upper limits on observed signal cross section, $\sigma_\text{obs}^\text{95}$, for the superpartners of the left-handed muons, $\tilde{\mu}_L$.
Upper limits on observed signal cross section, $\sigma_\text{obs}^\text{95}$, for the superpartners of the right-handed muons, $\tilde{\mu}_R$.
Upper limits on observed signal cross section, $\sigma_\text{obs}^\text{95}$, for the stau signal model. Staus, $\tilde{\tau}_{1,2}$ are the mixed states of the superpartners of the left- and right-handed $\tau$ leptons, with mixing angle $\sin\theta_{\tilde\tau}=0.95$.
Upper limits on observed signal cross section, $\sigma_\text{obs}^\text{95}$, for $\tilde{\tau}_L$ production, where $\tilde{\tau}_L$ is pure-state superpartner of the left-handed $\tau$.
The expected and observed yields in the signal regions. Combined statistical and systematic uncertainties are presented. Estimates are truncated at 0 if the size of measured systematic uncertainties would yield a negative result.
Reconstruction efficiency as a function of $|d_{0}|$ and $p_\text{T}$ for signal electrons. Monte Carlo samples with $\tilde{e}$ or $\tilde{\mu}$ with mass 400 GeV and 1 ns lifetime were used. Efficiency is defined as the number of leptons passing all signal requirements and matched to generator-level muons divided by the number of generator level leptons with $p_\text{T} > 65$ GeV, $|d_{0}| >$ 3 mm, and |$\eta$| $<$ 2.47 for electrons. No event-level selections are made. Reconstructed leptons must pass all quality criteria, including the cosmic veto. Electron selection scale factors are included on the reconstructed leptons. The overflow is not shown in these plots.
Reconstruction efficiency as a function of $|d_{0}|$ and $p_\text{T}$ for signal muons. Monte Carlo samples with $\tilde{e}$ or $\tilde{\mu}$ with mass 400 GeV and 1 ns lifetime were used. Efficiency is defined as the number of leptons passing all signal requirements and matched to generator-level muons divided by the number of generator level leptons with $p_\text{T} > 65$ GeV, $|d_{0}| >$ 3 mm, and |$\eta$| $<$ 2.5 for muons. No event-level selections are made. Reconstructed leptons must pass all quality criteria, including the cosmic veto. Muon selection scale factors are included on the reconstructed leptons. The overflow is not shown in these plots.
Acceptance for $\tilde{e}$ of various masses and lifetimes in SR-$ee$. Acceptance is defined as the number of accepted events at generator level in signal Monte Carlo simulation divided by the total number of events in the sample. To be accepted, events are required to have at least 2 truth electrons with $p_\text{T} > 65$ GeV, |$\eta$| $<$ 2.47, $|d_{0}| > 3$ mm, and $\Delta R_{\ell\ell} > 0.2$. Events are also required to fall into one of the acceptance regions of the triggers used. At generator level, events must have one of the following: one electron with $p_\text{T} >$ 160 GeV, 2 electrons each with $p_\text{T} >$ 60 GeV, or 1 muon with $p_\text{T} >$ 60 GeV and $|\eta| < 1.07$.
Acceptance for $\tilde{\mu}$ of various masses and lifetimes in SR-$\mu\mu$. Acceptance is defined as the number of accepted events at generator level in signal Monte Carlo simulation divided by the total number of events in the sample. To be accepted, events are required to have at least 2 truth muons with $p_\text{T} > 65$ GeV, |$\eta$| $<$ 2.5, $|d_{0}| > 3$ mm, and $\Delta R_{\ell\ell} > 0.2$. Events are also required to fall into one of the acceptance regions of the triggers used. At generator level, events must have one of the following: one electron with $p_\text{T} >$ 160 GeV, 2 electrons each with $p_\text{T} >$ 60 GeV, or 1 muon with $p_\text{T} >$ 60 GeV and $|\eta| < 1.07$.
Efficiency for $\tilde{e}$ of various masses and lifetimes in SR-$ee$. Efficiency is defined as the number of selected reconstruced events divided by the acceptance. To be accepted, events are required to have at least 2 truth electrons with $p_\text{T} > 65$ GeV, |$\eta$| $<$ 2.47, $|d_{0}| > 3$ mm, and $\Delta R_{\ell\ell} > 0.2$. Events are also required to fall into one of the acceptance regions of the triggers used. At generator level, events must have one of the following: one electron with $p_\text{T} >$ 160 GeV, 2 electrons each with $p_\text{T} >$ 60 GeV, or 1 muon with $p_\text{T} >$ 60 GeV and $|\eta| < 1.07$. To be selected, events must satisfy all signal region requirements.
Efficiency for $\tilde{\mu}$ of various masses and lifetimes in SR-$\mu\mu$. Efficiency is defined as the number of selected reconstruced events divided by the acceptance. To be accepted, events are required to have at least 2 truth muons with $p_\text{T} > 65$ GeV, |$\eta$| $<$ 2.5, $|d_{0}| > 3$ mm, and $\Delta R_{\ell\ell} > 0.2$. Events are also required to fall into one of the acceptance regions of the triggers used. At generator level, events must have one of the following: one electron with $p_\text{T} >$ 160 GeV, 2 electrons each with $p_\text{T} >$ 60 GeV, or 1 muon with $p_\text{T} >$ 60 GeV and $|\eta| < 1.07$. To be selected, events must satisfy all signal region requirements.
Acceptance as a function of the generator-level $p_\text{T}$ of the leading and subleading lepton in SR-$ee$ from $\tilde{e}$ decays. The plot is made from signal Monte Carlo events with $\tilde{\ell}$ with mass of 400 GeV and lifetime of 1 ns. To be accepted, events are required to have at least 2 truth leptons with $p_\text{T} > 65$ GeV, |$\eta$| $<$ 2.47 for electrons, $|d_{0}| > 3$ mm, and $\Delta R_{\ell\ell} > 0.2$. Events are also required to fall into one of the acceptance regions of the triggers used. At generator level, events must have one of the following: one electron with $p_\text{T} >$ 160 GeV, 2 electrons each with $p_\text{T} >$ 60 GeV, or 1 muon with $p_\text{T} >$ 60 GeV and $|\eta| < 1.07$. The overflow is not shown in these plots.
Acceptance as a function of the generator-level $p_\text{T}$ of the leading and subleading lepton in SR-$\mu\mu$ from $\tilde{\mu}$ decays. The plot is made from signal Monte Carlo events with $\tilde{\ell}$ with mass of 400 GeV and lifetime of 1 ns. To be accepted, events are required to have at least 2 truth leptons with $p_\text{T} > 65$ GeV, |$\eta$| $<$ 2.5 for muons, $|d_{0}| > 3$ mm, and $\Delta R_{\ell\ell} > 0.2$. Events are also required to fall into one of the acceptance regions of the triggers used. At generator level, events must have one of the following: one electron with $p_\text{T} >$ 160 GeV, 2 electrons each with $p_\text{T} >$ 60 GeV, or 1 muon with $p_\text{T} >$ 60 GeV and $|\eta| < 1.07$. The overflow is not shown in these plots.
Acceptance for $\tilde{\tau}$ of various masses and lifetimes in SR-$ee$. Acceptance is defined as the number of accepted events at generator level in signal Monte Carlo simulation divided by the total number of events in the sample. To be accepted, events are required to have at least 2 truth electrons with $p_\text{T} > 65$ GeV, |$\eta$| $<$ 2.47, $|d_{0}| > 3$ mm, and $\Delta R_{\ell\ell} > 0.2$. Events are also required to fall into one of the acceptance regions of the triggers used. At generator level, events must have one of the following: one electron with $p_\text{T} >$ 160 GeV, 2 electrons each with $p_\text{T} >$ 60 GeV, or 1 muon with $p_\text{T} >$ 60 GeV and $|\eta| < 1.07$.
Acceptance for $\tilde{\tau}$ of various masses and lifetimes in SR-$e\mu$. Acceptance is defined as the number of accepted events at generator level in signal Monte Carlo simulation divided by the total number of events in the sample. To be accepted, events are required to have at least 2 truth leptons with $p_\text{T} > 65$ GeV, |$\eta$| $<$ 2.5 (2.47) for muons (electrons), $|d_{0}| > 3$ mm, and $\Delta R_{\ell\ell} > 0.2$. Events are also required to fall into one of the acceptance regions of the triggers used. At generator level, events must have one of the following: one electron with $p_\text{T} >$ 160 GeV, 2 electrons each with $p_\text{T} >$ 60 GeV, or 1 muon with $p_\text{T} >$ 60 GeV and $|\eta| < 1.07$.
Acceptance for $\tilde{\tau}$ of various masses and lifetimes in SR-$\mu\mu$. Acceptance is defined as the number of accepted events at generator level in signal Monte Carlo simulation divided by the total number of events in the sample. To be accepted, events are required to have at least 2 truth muons with $p_\text{T} > 65$ GeV, |$\eta$| $<$ 2.5, $|d_{0}| > 3$ mm, and $\Delta R_{\ell\ell} > 0.2$. Events are also required to fall into one of the acceptance regions of the triggers used. At generator level, events must have one of the following: one electron with $p_\text{T} >$ 160 GeV, 2 electrons each with $p_\text{T} >$ 60 GeV, or 1 muon with $p_\text{T} >$ 60 GeV and $|\eta| < 1.07$.
Efficiency for $\tilde{\tau}$ of various masses and lifetimes in SR-$ee$. Efficiency is defined as the number of selected reconstruced events divided by the acceptance. To be accepted, events are required to have at least 2 truth electrons with $p_\text{T} > 65$ GeV, |$\eta$| $<$ 2.47, $|d_{0}| > 3$ mm, and $\Delta R_{\ell\ell} > 0.2$. Events are also required to fall into one of the acceptance regions of the triggers used. At generator level, events must have one of the following: one electron with $p_\text{T} >$ 160 GeV, 2 electrons each with $p_\text{T} >$ 60 GeV, or 1 muon with $p_\text{T} >$ 60 GeV and $|\eta| < 1.07$. To be selected, events must satisfy all signal region requirements.
Efficiency for $\tilde{\tau}$ of various masses and lifetimes in SR-$e\mu$. Efficiency is defined as the number of selected reconstruced events divided by the acceptance. To be accepted, events are required to have at least 2 truth leptons with $p_\text{T} > 65$ GeV, |$\eta$| $<$ 2.5 (2.47) for muons (electrons), $|d_{0}| > 3$ mm, and $\Delta R_{\ell\ell} > 0.2$. Events are also required to fall into one of the acceptance regions of the triggers used. At generator level, events must have one of the following: one electron with $p_\text{T} >$ 160 GeV, 2 electrons each with $p_\text{T} >$ 60 GeV, or 1 muon with $p_\text{T} >$ 60 GeV and $|\eta| < 1.07$. To be selected, events must satisfy all signal region requirements.
Efficiency for $\tilde{\tau}$ of various masses and lifetimes in SR-$\mu\mu$. Efficiency is defined as the number of selected reconstruced events divided by the acceptance. To be accepted, events are required to have at least 2 truth muons with $p_\text{T} > 65$ GeV, |$\eta$| $<$ 2.5, $|d_{0}| > 3$ mm, and $\Delta R_{\ell\ell} > 0.2$. Events are also required to fall into one of the acceptance regions of the triggers used. At generator level, events must have one of the following: one electron with $p_\text{T} >$ 160 GeV, 2 electrons each with $p_\text{T} >$ 60 GeV, or 1 muon with $p_\text{T} >$ 60 GeV and $|\eta| < 1.07$. To be selected, events must satisfy all signal region requirements.
Acceptance as a function of the generator-level $p_\text{T}$ of the leading and subleading lepton in SR-$e\mu$ from $\tilde{\tau}$ decays. The plot is made from signal Monte Carlo events with $\tilde{\ell}$ with mass of 400 GeV and lifetime of 1 ns. To be accepted, events are required to have at least 2 truth leptons with $p_\text{T} > 65$ GeV, |$\eta$| $<$ 2.5 (2.47) for muons (electrons), $|d_{0}| > 3$ mm, and $\Delta R_{\ell\ell} > 0.2$. Events are also required to fall into one of the acceptance regions of the triggers used. At generator level, events must have one of the following: one electron with $p_\text{T} >$ 160 GeV, 2 electrons each with $p_\text{T} >$ 60 GeV, or 1 muon with $p_\text{T} >$ 60 GeV and $|\eta| < 1.07$. The overflow is not shown in these plots.
Observed 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\ell})$ plane where all slepton flavors and chiralities are mass degenerate.
Expected 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\ell})$ plane where all slepton flavors and chiralities are mass degenerate.
Observed 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\ell})$ plane in SR-$ee$ targeting selectron production. Selectrons ($\tilde{e}_{L, R}$) refer to the scalar superpartners of left- and right-handed electrons, which are assumed to be mass degenerate.
Expected 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\ell})$ plane in SR-$ee$ targeting selectron production. Selectrons ($\tilde{e}_{L, R}$) refer to the scalar superpartners of left- and right-handed electrons, which are assumed to be mass degenerate.
Observed 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\ell})$ plane in SR-$ee$ targeting selectron production. Selectrons ($\tilde{e}_{L}$) refer to the scalar superpartners of left-handed electrons.
Expected 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\ell})$ plane in SR-$ee$ targeting selectron production. Selectrons ($\tilde{e}_{L}$) refer to the scalar superpartners of left-handed electrons.
Observed 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\ell})$ plane in SR-$ee$ targeting selectron production. Selectrons ($\tilde{e}_{R}$) refer to the scalar superpartners of right-handed electrons. Purple denotes the region excluded by LEP.
Expected 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\ell})$ plane in SR-$ee$ targeting selectron production. Selectrons ($\tilde{e}_{R}$) refer to the scalar superpartners of right-handed electrons. Purple denotes the region excluded by LEP.
Observed 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\ell})$ plane in SR-$\mu\mu$ targeting smuon production. Smuons ($\tilde{\mu}_{L, R}$) refer to the scalar superpartners of left- and right-handed muons, which are assumed to be mass degenerate.
Expected 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\ell})$ plane in SR-$\mu\mu$ targeting smuon production. Smuons ($\tilde{\mu}_{L, R}$) refer to the scalar superpartners of left- and right-handed muons, which are assumed to be mass degenerate.
Expected 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\ell})$ plane in SR-$\mu\mu$ targeting smuon production. Smuons ($\tilde{\mu}_{L}$) refer to the scalar superpartners of left-handed muons.
Observed 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\ell})$ plane in SR-$\mu\mu$ targeting smuon production. Smuons ($\tilde{\mu}_{L}$) refer to the scalar superpartners of left-handed muons.
Observed 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\ell})$ plane in SR-$\mu\mu$ targeting smuon production. Smuons ($\tilde{\mu}_{R}$) refer to the scalar superpartners of right-handed muons. Purple denotes the region excluded by LEP.
Expected 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\ell})$ plane in SR-$\mu\mu$ targeting smuon production. Smuons ($\tilde{\mu}_{R}$) refer to the scalar superpartners of right-handed muons. Purple denotes the region excluded by LEP.
Observed 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\tau})$ plane. Staus, $\tilde{\tau}_{1,2}$ are the mixed states of the superpartners of the left- and right-handed $\tau$ leptons, with mixing angle $\sin(\theta_{\tilde\tau})=0.95$, which are assumed to be mass degenerate.
Expected 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\tau})$ plane. Staus, $\tilde{\tau}_{1,2}$ are the mixed states of the superpartners of the left- and right-handed $\tau$ leptons, with mixing angle $\sin(\theta_{\tilde\tau})=0.95$, which are assumed to be mass degenerate.
Observed 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\tau}_L)$ plane, where $\tilde{\tau}_L$ is the pure-state super-partner of the left-handed $\tau$. Purple denotes the region excluded by LEP. This result does not present signficant sensitivity to the pure-state superpartner of the right-handed $\tau$.
Expected 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\tau}_L)$ plane, where $\tilde{\tau}_L$ is the pure-state super-partner of the left-handed $\tau$. Purple denotes the region excluded by LEP. This result does not present signficant sensitivity to the pure-state superpartner of the right-handed $\tau$.
A search for dark matter is conducted in final states containing a photon and missing transverse momentum in proton$-$proton collisions at $\sqrt{s}$ = 13 TeV. The data, collected during 2015$-$2018 by the ATLAS experiment at the CERN LHC, correspond to an integrated luminosity of 139 fb$^{-1}$. No deviations from the predictions of the Standard Model are observed and 95% confidence-level upper limits between 2.45 fb and 0.5 fb are set on the visible cross section for contributions from physics beyond the Standard Model, in different ranges of the missing transverse momentum. The results are interpreted as 95% confidence-level limits in models where weakly interacting dark-matter candidates are pair-produced via an s-channel axial-vector or vector mediator. Dark-matter candidates with masses up to 415 (580) GeV are excluded for axial-vector (vector) mediators, while the maximum excluded mass of the mediator is 1460 (1470) GeV. In addition, the results are expressed in terms of 95% confidence-level limits on the parameters of a model with an axion-like particle produced in association with a photon, and are used to constrain the coupling $g_{aZ\gamma}$ of an axion-like particle to the electroweak gauge bosons.
Distribution of $E^{miss}_T$ in data and for the expected SM background in the SRs after performing the 'simplified shape fit'. The error bars are statistical, and the dashed band includes statistical and systematic uncertainties determined by the fit. The expectations for the simplified model for two different values of $m_{\chi}$ and $m_{med}$, and with $g_{q}=0.25$ and $g_{\chi}=1.0$ and for the ALP model are also shown. The lower panel shows the ratio of data to expected background event yields.
Distribution of $E^{miss}_T$ in data and for the expected SM background in the SRs after performing the 'simplified shape fit'. Overflows are included in the fourth bin of each distribution. The error bars are statistical, and the dashed band includes statistical and systematic uncertainties determined by the fit. The expectations for the simplified model for two different values of $m_{\chi}$ and $m_{med}$, and with $g_{q}=0.25$ and $g_{\chi}=1.0$ and for the ALP model are also shown. The lower panel shows the ratio of data to expected background event yields.
Distribution of $E^{miss}_T$ in data and for the expected SM background in the Single-Muon CR after performing the 'simplified shape fit'. The $E^{miss}_T$ calculation in this CR does not include the muon contribution. The error bars are statistical, and the dashed band includes statistical and systematic uncertainties determined by the fit. The lower panel shows the ratio of data to expected background event yields.
Distribution of $E^{miss}_T$ in data and for the expected SM background in the Single-Muon CR after performing the 'simplified shape fit'. Overflows are included in the fourth bin of each distribution. The $E^{miss}_T$ calculation in this CR does not include the muon contribution. The error bars are statistical, and the dashed band includes statistical and systematic uncertainties determined by the fit. The lower panel shows the ratio of data to expected background event yields.
Distribution of $E^{miss}_T$ in data and for the expected SM background in the Two-Muon CR after performing the 'simplified shape fit'. The $E^{miss}_T$ calculation in this CR does not include the muon contribution. The error bars are statistical, and the dashed band includes statistical and systematic uncertainties determined by the fit. The lower panel shows the ratio of data to expected background event yields.
Distribution of $E^{miss}_T$ in data and for the expected SM background in the Two-Muon CR after performing the 'simplified shape fit'. Overflows are included in the fourth bin of each distribution. The $E^{miss}_T$ calculation in this CR does not include the muon contribution. The error bars are statistical, and the dashed band includes statistical and systematic uncertainties determined by the fit. The lower panel shows the ratio of data to expected background event yields.
Distribution of $E^{miss}_T$ in data and for the expected SM background in the Two-Electron CR after performing the 'simplified shape fit'. The $E^{miss}_$ calculation in this CR does not include electron contribution. The error bars are statistical, and the dashed band includes statistical and systematic uncertainties determined by the fit. The lower panel shows the ratio of data to expected background event yields.
Distribution of $E^{miss}_T$ in data and for the expected SM background in the Two-Electron CR after performing the 'simplified shape fit'. Overflows are included in the fourth bin of each distribution. The $E^{miss}_T$ calculation in this CR does not include electron contribution. The error bars are statistical, and the dashed band includes statistical and systematic uncertainties determined by the fit. The lower panel shows the ratio of data to expected background event yields.
The observed exclusion contours on the $m_{\chi} - m_{med}$ plane for a simplified DM model involving an axial-vector mediator with couplings $g_{\chi}$ = 1, $g_q$ = 0.25 and $g_l$ = 0.
The observed exclusion contours on the $m_{\chi} - m_{med}$ plane for a simplified DM model involving an axial-vector mediator with couplings $g_{\chi}$ = 1, $g_q$ = 0.25 and $g_l$ = 0.
The expected exclusion contours on the $m_{\chi} - m_{med}$ plane for a simplified DM model involving an axial-vector mediator with couplings $g_{\chi}$ = 1, $g_q$ = 0.25 and $g_l$ = 0.
The expected exclusion contours on the $m_{\chi} - m_{med}$ plane for a simplified DM model involving an axial-vector mediator with couplings $g_{\chi}$ = 1, $g_q$ = 0.25 and $g_l$ = 0.
The expected + 1 sigma exclusion contours on the $m_{\chi} - m_{med}$ plane for a simplified DM model involving an axial-vector mediator with couplings $g_{\chi}$ = 1, $g_q$ = 0.25 and $g_l$ = 0.
The expected + 1 sigma exclusion contours on the $m_{\chi} - m_{med}$ plane for a simplified DM model involving an axial-vector mediator with couplings $g_{\chi}$ = 1, $g_q$ = 0.25 and $g_l$ = 0.
The expected - 1 sigma exclusion contours on the $m_{\chi} - m_{med}$ plane for a simplified DM model involving an axial-vector mediator with couplings $g_{\chi}$ = 1, $g_q$ = 0.25 and $g_l$ = 0.
The expected - 1 sigma exclusion contours on the $m_{\chi} - m_{med}$ plane for a simplified DM model involving an axial-vector mediator with couplings $g_{\chi}$ = 1, $g_q$ = 0.25 and $g_l$ = 0.
The observed exclusion contours on the $m_{\chi} - m_{med}$ plane for a simplified DM model involving an axial-vector mediator with couplings $g_{\chi}$ = 1, $g_q$ = 0.1 and $g_l$ = 0.1.
The observed exclusion contours on the $m_{\chi} - m_{med}$ plane for a simplified DM model involving an axial-vector mediator with couplings $g_{\chi}$ = 1, $g_q$ = 0.1 and $g_l$ = 0.1.
The expected exclusion contours on the $m_{\chi} - m_{med}$ plane for a simplified DM model involving an axial-vector mediator with couplings $g_{\chi}$ = 1, $g_q$ = 0.1 and $g_l$ = 0.1.
The expected exclusion contours on the $m_{\chi} - m_{med}$ plane for a simplified DM model involving an axial-vector mediator with couplings $g_{\chi}$ = 1, $g_q$ = 0.1 and $g_l$ = 0.1.
The expected + 1 sigma exclusion contours on the $m_{\chi} - m_{med}$ plane for a simplified DM model involving an axial-vector mediator with couplings $g_{\chi}$ = 1, $g_q$ = 0.1 and $g_l$ = 0.1.
The expected + 1 sigma exclusion contours on the $m_{\chi} - m_{med}$ plane for a simplified DM model involving an axial-vector mediator with couplings $g_{\chi}$ = 1, $g_q$ = 0.1 and $g_l$ = 0.1.
The expected - 1 sigma exclusion contours on the $m_{\chi} - m_{med}$ plane for a simplified DM model involving an axial-vector mediator with couplings $g_{\chi}$ = 1, $g_q$ = 0.1 and $g_l$ = 0.1.
The expected - 1 sigma exclusion contours on the $m_{\chi} - m_{med}$ plane for a simplified DM model involving an axial-vector mediator with couplings $g_{\chi}$ = 1, $g_q$ = 0.1 and $g_l$ = 0.1.
The observed exclusion contours on the $m_{\chi} - m_{med}$ plane for a vector mediator with couplings $g_{\chi}$ = 1, $g_q$ = 0.25 and $g_l$ = 0.
The observed exclusion contours on the $m_{\chi} - m_{med}$ plane for a vector mediator with couplings $g_{\chi}$ = 1, $g_q$ = 0.25 and $g_l$ = 0.
The expected exclusion contours on the $m_{\chi} - m_{med}$ plane for a vector mediator with couplings $g_{\chi}$ = 1, $g_q$ = 0.25 and $g_l$ = 0.
The expected exclusion contours on the $m_{\chi} - m_{med}$ plane for a vector mediator with couplings $g_{\chi}$ = 1, $g_q$ = 0.25 and $g_l$ = 0.
The expected + 1 sigma exclusion contours on the $m_{\chi} - m_{med}$ plane for a vector mediator with couplings $g_{\chi}$ = 1, $g_q$ = 0.25 and $g_l$ = 0.
The expected + 1 sigma exclusion contours on the $m_{\chi} - m_{med}$ plane for a vector mediator with couplings $g_{\chi}$ = 1, $g_q$ = 0.25 and $g_l$ = 0.
The expected - 1 sigma exclusion contours on the $m_{\chi} - m_{med}$ plane for a vector mediator with couplings $g_{\chi}$ = 1, $g_q$ = 0.25 and $g_l$ = 0.
The expected - 1 sigma exclusion contours on the $m_{\chi} - m_{med}$ plane for a vector mediator with couplings $g_{\chi}$ = 1, $g_q$ = 0.25 and $g_l$ = 0.
The observed exclusion contours on the $m_{\chi} - m_{med}$ plane for a vector mediator with couplings and $g_{\chi}$ = 1, $g_q$ = 0.1 and $g_l$ = 0.01
The observed exclusion contours on the $m_{\chi} - m_{med}$ plane for a vector mediator with couplings and $g_{\chi}$ = 1, $g_q$ = 0.1 and $g_l$ = 0.01
The expected exclusion contours on the $m_{\chi} - m_{med}$ plane for a vector mediator with couplings $g_{\chi}$ = 1, $g_q$ = 0.1 and $g_l$ = 0.01.
The expected exclusion contours on the $m_{\chi} - m_{med}$ plane for a vector mediator with couplings $g_{\chi}$ = 1, $g_q$ = 0.1 and $g_l$ = 0.01.
The expected + 1 sigma exclusion contours on the $m_{\chi} - m_{med}$ plane for a vector mediator with couplings $g_{\chi}$ = 1, $g_q$ = 0.1 and $g_l$ = 0.01.
The expected + 1 sigma exclusion contours on the $m_{\chi} - m_{med}$ plane for a vector mediator with couplings $g_{\chi}$ = 1, $g_q$ = 0.1 and $g_l$ = 0.01.
The expected - 1 sigma exclusion contours on the $m_{\chi} - m_{med}$ plane for a vector mediator with couplings $g_{\chi}$ = 1, $g_q$ = 0.1 and $g_l$ = 0.01.
The expected - 1 sigma exclusion contours on the $m_{\chi} - m_{med}$ plane for a vector mediator with couplings $g_{\chi}$ = 1, $g_q$ = 0.1 and $g_l$ = 0.01.
The 90% CL exclusion limit on $\chi$-proton spin-dependent scattering cross section in an axial-vector model with couplings $g_{\chi}$ = 1, $g_q$ = 0.25 and $g_l$ = 0 as a function of the dark-matter mass $m_{\chi}$.
The 90% CL exclusion limit on $\chi$-proton spin-dependent scattering cross section in an axial-vector model with couplings $g_{\chi}$ = 1, $g_q$ = 0.25 and $g_l$ = 0 as a function of the dark-matter mass $m_{\chi}$. The 90% CL exclusion limit is displayed only in the regime where the theory is perturbative.
The 90% CL exclusion limit on $\chi$-neutron spin-dependent scattering cross section in an axial-vector model with couplings $g_{\chi}$ = 1, $g_q$ = 0.25 and $g_l$ = 0 as a function of the dark-matter mass $m_{\chi}$.
The 90% CL exclusion limit on $\chi$-neutron spin-dependent scattering cross section in an axial-vector model with couplings $g_{\chi}$ = 1, $g_q$ = 0.25 and $g_l$ = 0 as a function of the dark-matter mass $m_{\chi}$. The 90% CL exclusion limit is displayed only in the regime where the theory is perturbative.
The 90% CL exclusion limit on $\chi$-nucleon spin-independent scattering cross section in a vector model with couplings $g_{\chi}$ = 1, $g_q$ = 0.25 and $g_l$ = 0 as a function of the dark-matter mass $m_{\chi}$.
The 90% CL exclusion limit on $\chi$-nucleon spin-independent scattering cross section in a vector model with couplings $g_{\chi}$ = 1, $g_q$ = 0.25 and $g_l$ = 0 as a function of the dark-matter mass $m_{\chi}$.
Observed and expected exclusion at 95% CL on the coupling $c_W$ as a function of the effective scale $f_a$ for an ALP mass of 1 MeV.
Observed and expected exclusion at 95% CL on the coupling $c_W$ as a function of the effective scale $f_a$ for an ALP mass of 1 MeV.
The observed 95% CL upper limits on signal strength $\mu$, the ratio of the experimental limit to the predicted signal cross section, for a simplified model of dark matter production involving an axial-vector operator and couplings $g_{\chi}$ = 1, $g_q$ = 0.25 and $g_l$ = 0 as a function of the mass of the dark matter, $m_{\chi}$ and the mass of the axial-vector mediator, $m_{med}$.
The observed 95% CL upper limits on signal strength $\mu$, the ratio of the experimental limit to the predicted signal cross section, for a simplified model of dark matter production involving an axial-vector operator and couplings $g_{\chi}$ = 1, $g_q$ = 0.25 and $g_l$ = 0 as a function of the mass of the dark matter, $m_{\chi}$ and the mass of the axial-vector mediator, $m_{med}$.
The observed 95% CL upper limits on cross section for a simplified model of dark matter production involving an axial-vector operator and couplings $g_{\chi}$ = 1, $g_q$ = 0.25 and $g_l$ = 0 as a function of the mass of the dark matter, $m_{\chi}$ and the mass of the axial-vector mediator, $m_{med}$.
The observed 95% CL upper limits on cross section for a simplified model of dark matter production involving an axial-vector operator and couplings $g_{\chi}$ = 1, $g_q$ = 0.25 and $g_l$ = 0 as a function of the mass of the dark matter, $m_{\chi}$ and the mass of the axial-vector mediator, $m_{med}$.
Acceptance in % for a simplified model of dark matter production involving an axial-vector operator with couplings $g_{\chi}$ = 1, $g_q$ = 0.25 and $g_l$ = 0 for different values of $m_{\chi}$ and $m_{med}$ in the four inclusive signal regions.
Acceptance in % for a simplified model of dark matter production involving an axial-vector operator with couplings $g_{\chi}$ = 1, $g_q$ = 0.25 and $g_l$ = 0 for different values of $m_{\chi}$ and $m_{med}$ in the four inclusive signal regions.
Acceptance in % for a simplified model of dark matter production involving an axial-vector operator with couplings $g_{\chi}$ = 1, $g_q$ = 0.25 and $g_l$ = 0 for different values of $m_{\chi}$ and $m_{med}$ in the three exclusive signal regions.
Acceptance in % for a simplified model of dark matter production involving an axial-vector operator with couplings $g_{\chi}$ = 1, $g_q$ = 0.25 and $g_l$ = 0 for different values of $m_{\chi}$ and $m_{med}$ in the three exclusive signal regions.
Efficiencies for a simplified model of dark matter production involving an axial-vector operator with couplings $g_{\chi}$ = 1, $g_q$ = 0.25 and $g_l$ = 0 for different values of $m_{\chi}$ and $m_{med}$ in the four inclusive signal regions.
Efficiencies for a simplified model of dark matter production involving an axial-vector operator with couplings $g_{\chi}$ = 1, $g_q$ = 0.25 and $g_l$ = 0 for different values of $m_{\chi}$ and $m_{med}$ in the four inclusive signal regions.
Efficiencies for a simplified model of dark matter production involving an axial-vector operator with couplings $g_{\chi}$ = 1, $g_q$ = 0.25 and $g_l$ = 0 for different values of $m_{\chi}$ and $m_{med}$ in the three exclusive signal regions.
Efficiencies for a simplified model of dark matter production involving an axial-vector operator with couplings $g_{\chi}$ = 1, $g_q$ = 0.25 and $g_l$ = 0 for different values of $m_{\chi}$ and $m_{med}$ in the three exclusive signal regions.
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 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-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 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 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 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-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.
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