Distributions of $s_{\text{T}}$ in the single-tau one-bin SR. The stacked histograms show the various SM background contributions. The hatched band indicates the total statistical and systematic uncertainty of the SM background. The $t\bar{t}$ (2 real $\tau$) and $t\bar{t}$ (1 real $\tau$) as well as the single-top background contributions are scaled with the normalization factors obtained from the background-only fit. Minor backgrounds are grouped together and denoted as 'Other'. This includes $t\bar{t}$-fake, single top, and other top (di-tau channel) or $t\bar{t}$-fake, $t\bar{t}+H$, multiboson, and other top (single-tau channel). The overlaid dotted lines show the additional contributions for signal scenarios close to the expected exclusion contour with the particle type and the mass and $\beta$ parameters for the simplified models indicated in the legend. For the leptoquark signal model the shapes of the distributions for $\text{LQ}_{3}^{\text{d}}$ and $\text{LQ}_{3}^{\text{v}}$ (not shown) are similar to that of $\text{LQ}_{3}^{\text{u}}$. The rightmost bin includes the overflow.

Distributions of $m_{\text{T}}(\tau)$ in the single-tau one-bin SR. The stacked histograms show the various SM background contributions. The hatched band indicates the total statistical and systematic uncertainty of the SM background. The $t\bar{t}$ (2 real $\tau$) and $t\bar{t}$ (1 real $\tau$) as well as the single-top background contributions are scaled with the normalization factors obtained from the background-only fit. Minor backgrounds are grouped together and denoted as 'Other'. This includes $t\bar{t}$-fake, single top, and other top (di-tau channel) or $t\bar{t}$-fake, $t\bar{t}+H$, multiboson, and other top (single-tau channel). The overlaid dotted lines show the additional contributions for signal scenarios close to the expected exclusion contour with the particle type and the mass and $\beta$ parameters for the simplified models indicated in the legend. For the leptoquark signal model the shapes of the distributions for $\text{LQ}_{3}^{\text{d}}$ and $\text{LQ}_{3}^{\text{v}}$ (not shown) are similar to that of $\text{LQ}_{3}^{\text{u}}$. The rightmost bin includes the overflow.

Distributions of $\Sigma m_{\text{T}}(b_{1,2})$ in the single-tau $p_{\text{T}}(\tau)$-binned SR. The stacked histograms show the various SM background contributions. The hatched band indicates the total statistical and systematic uncertainty of the SM background. The $t\bar{t}$ (2 real $\tau$) and $t\bar{t}$ (1 real $\tau$) as well as the single-top background contributions are scaled with the normalization factors obtained from the background-only fit. Minor backgrounds are grouped together and denoted as 'Other'. This includes $t\bar{t}$-fake, single top, and other top (di-tau channel) or $t\bar{t}$-fake, $t\bar{t}+H$, multiboson, and other top (single-tau channel). The overlaid dotted lines show the additional contributions for signal scenarios close to the expected exclusion contour with the particle type and the mass and $\beta$ parameters for the simplified models indicated in the legend. For the leptoquark signal model the shapes of the distributions for $\text{LQ}_{3}^{\text{d}}$ and $\text{LQ}_{3}^{\text{v}}$ (not shown) are similar to that of $\text{LQ}_{3}^{\text{u}}$. The rightmost bin includes the overflow.

Distributions of $p_{\text{T}}(\tau)$ in the single-tau $p_{\text{T}}(\tau)$-binned SR. The stacked histograms show the various SM background contributions. The hatched band indicates the total statistical and systematic uncertainty of the SM background. The $t\bar{t}$ (2 real $\tau$) and $t\bar{t}$ (1 real $\tau$) as well as the single-top background contributions are scaled with the normalization factors obtained from the background-only fit. Minor backgrounds are grouped together and denoted as 'Other'. This includes $t\bar{t}$-fake, single top, and other top (di-tau channel) or $t\bar{t}$-fake, $t\bar{t}+H$, multiboson, and other top (single-tau channel). The overlaid dotted lines show the additional contributions for signal scenarios close to the expected exclusion contour with the particle type and the mass and $\beta$ parameters for the simplified models indicated in the legend. For the leptoquark signal model the shapes of the distributions for $\text{LQ}_{3}^{\text{d}}$ and $\text{LQ}_{3}^{\text{v}}$ (not shown) are similar to that of $\text{LQ}_{3}^{\text{u}}$. The rightmost bin includes the overflow.

Observed event yields in data ('Observed') and expected event yields for SM background processes obtained from the background-only fit ('Total bkg.' and rows below) in the signal regions of the di-tau and single-tau channels. The quoted uncertainties include both the statistical and systematic uncertainties and are truncated at zero yield. By construction, no $t\bar{t}$ (2 real $\tau$) events can pass the selections in the single-tau channel. As the individual uncertainties are correlated, they do not add in quadrature to equal the total background uncertainty.

From left to right: upper limits at the 95% confidence level (CL) on the visible cross section ($\sigma_\text{vis}$) and on the number of signal events ($S_{\text{obs}}^{95}$). The third column ($S_{\text{exp}}^{95}$) shows the upper limit at the 95% CL on the number of signal events, given the expected number (and $\pm 1\,\sigma$ excursions on the expectation) of background events. The last two columns indicate the confidence level observed for the background-only hypothesis ($\text{CL}_{b}$), the discovery $p$-value ($p(s=0)$) and the significance ($Z$). In the di-tau SR, where fewer events are observed than predicted by the fitted background estimate, the $p$-value is capped at 0.5.

Expected and observed exclusion contours at the 95% confidence level for the vector third-generation leptoquark signal model, as a function of the mass $m(\text{LQ}_{3}^{\text{v}})$ and the branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ into a quark and a charged lepton. The plot shows the exclusion contour for the minimal-coupling scenario. The limits are derived from the binned single-tau signal region.

Expected and observed exclusion contours at the 95% confidence level for the vector third-generation leptoquark signal model, as a function of the mass $m(\text{LQ}_{3}^{\text{v}})$ and the branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ into a quark and a charged lepton. The plot shows the exclusion contour for the minimal-coupling scenario. The limits are derived from the binned single-tau signal region.

Expected and observed exclusion contours at the 95% confidence level for the vector third-generation leptoquark signal model, as a function of the mass $m(\text{LQ}_{3}^{\text{v}})$ and the branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ into a quark and a charged lepton. The plot shows the exclusion contour for vector leptoquarks with additional gauge couplings. The limits are derived from the binned single-tau signal region.

Expected and observed exclusion contours at the 95% confidence level for the vector third-generation leptoquark signal model, as a function of the mass $m(\text{LQ}_{3}^{\text{v}})$ and the branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ into a quark and a charged lepton. The plot shows the exclusion contour for vector leptoquarks with additional gauge couplings. The limits are derived from the binned single-tau signal region.

Exclusion contours at the 95% confidence level for the stop-stau signal model as a function of the masses of the top squark $m(\tilde{t}_{1})$ and of the tau slepton $m(\tilde{\tau}_{1})$. Expected and observed limits are shown for the present search in comparison to observed limits from previous ATLAS analyses based on data from Run-1 of the LHC at $\sqrt{s} = 8$ TeV [Eur. Phys. J. C 76 (2016)] and on a partial dataset from Run 2 at $\sqrt{s} = 13$ TeV [Phys. Rev. D 98 (2018) 032008]. The green band indicates the limit on the mass of the tau slepton (for a massless LSP) from the LEP experiments.

Exclusion contours at the 95% confidence level for the stop-stau signal model as a function of the masses of the top squark $m(\tilde{t}_{1})$ and of the tau slepton $m(\tilde{\tau}_{1})$. Expected and observed limits are shown for the present search in comparison to observed limits from previous ATLAS analyses based on data from Run-1 of the LHC at $\sqrt{s} = 8$ TeV [Eur. Phys. J. C 76 (2016)] and on a partial dataset from Run 2 at $\sqrt{s} = 13$ TeV [Phys. Rev. D 98 (2018) 032008]. The green band indicates the limit on the mass of the tau slepton (for a massless LSP) from the LEP experiments.

Expected and observed exclusion contours at the 95% confidence level for the scalar third-generation leptoquark signal model, as a function of the mass $m(\text{LQ}_{3}^{\text{u}})$ and the branching fraction $B(\text{LQ}_{3}^{\text{u}} \rightarrow q\ell)$ into a quark and a charged lepton. The plot shows the exclusion contour for up-type leptoquarks $\text{LQ}_{3}^{\text{u}})$ with charge $+2/3e$. The limits are derived from the binned single-tau signal region. Shown in gray for comparison are the observed exclusion-limit contours from the previous ATLAS publication that targets the same leptoquark models but is based on a subset of the Run-2 data [JHEP 06 (2019) 144]. In this previous publication five different analyses are considered that target not only the final state studied here but also the final states that correspond to a branching fraction $B(\text{LQ}_{3}^{\text{u}} \rightarrow q\ell)$ of 0 or 1, leading to the concave shapes of the gray exclusion contours.

Expected and observed exclusion contours at the 95% confidence level for the scalar third-generation leptoquark signal model, as a function of the mass $m(\text{LQ}_{3}^{\text{u}})$ and the branching fraction $B(\text{LQ}_{3}^{\text{u}} \rightarrow q\ell)$ into a quark and a charged lepton. The plot shows the exclusion contour for up-type leptoquarks $\text{LQ}_{3}^{\text{u}})$ with charge $+2/3e$. The limits are derived from the binned single-tau signal region. Shown in gray for comparison are the observed exclusion-limit contours from the previous ATLAS publication that targets the same leptoquark models but is based on a subset of the Run-2 data [JHEP 06 (2019) 144]. In this previous publication five different analyses are considered that target not only the final state studied here but also the final states that correspond to a branching fraction $B(\text{LQ}_{3}^{\text{u}} \rightarrow q\ell)$ of 0 or 1, leading to the concave shapes of the gray exclusion contours.

Expected and observed exclusion contours at the 95% confidence level for the scalar third-generation leptoquark signal model, as a function of the mass $m(\text{LQ}_{3}^{\text{d}})$ and the branching fraction $B(\text{LQ}_{3}^{\text{d}} \rightarrow q\ell)$ into a quark and a charged lepton. The plot shows the exclusion contour for down-type leptoquarks $\text{LQ}_{3}^{\text{d}})$ with charge $-1/3e$. The limits are derived from the binned single-tau signal region. Shown in gray for comparison are the observed exclusion-limit contours from the previous ATLAS publication that targets the same leptoquark models but is based on a subset of the Run-2 data [JHEP 06 (2019) 144]. In this previous publication five different analyses are considered that target not only the final state studied here but also the final states that correspond to a branching fraction $B(\text{LQ}_{3}^{\text{d}} \rightarrow q\ell)$ of 0 or 1, leading to the concave shapes of the gray exclusion contours.

Expected and observed exclusion contours at the 95% confidence level for the scalar third-generation leptoquark signal model, as a function of the mass $m(\text{LQ}_{3}^{\text{d}})$ and the branching fraction $B(\text{LQ}_{3}^{\text{d}} \rightarrow q\ell)$ into a quark and a charged lepton. The plot shows the exclusion contour for down-type leptoquarks $\text{LQ}_{3}^{\text{d}})$ with charge $-1/3e$. The limits are derived from the binned single-tau signal region. Shown in gray for comparison are the observed exclusion-limit contours from the previous ATLAS publication that targets the same leptoquark models but is based on a subset of the Run-2 data [JHEP 06 (2019) 144]. In this previous publication five different analyses are considered that target not only the final state studied here but also the final states that correspond to a branching fraction $B(\text{LQ}_{3}^{\text{d}} \rightarrow q\ell)$ of 0 or 1, leading to the concave shapes of the gray exclusion contours.

Upper limits on the signal cross section at the 95 % confidence level for the stop-stau signal model.

Upper limits on the signal cross section at the 95 % confidence level for the scalar third-generation leptoquark signal model with up-type leptoquarks.

Upper limits on the signal cross section at the 95 % confidence level for the scalar third-generation leptoquark signal model with down-type leptoquarks.

Upper limits on the signal cross section at the 95 % confidence level for the vector third-generation leptoquark signal model with minimal coupling (MC).

Upper limits on the signal cross section at the 95 % confidence level for the vector third-generation leptoquark signal model with additional gauge couplings (YM).

Acceptance of the one-bin signal region of the single-tau channel for pair production of up-type leptoquarks $\text{LQ}_{3}^{\text{u}}$.

Efficiency of the one-bin signal region of the single-tau channel for pair production of up-type leptoquarks $\text{LQ}_{3}^{\text{u}}$. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{u}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.

Acceptance of the first bin of the multi-bin signal region (50 GeV $< p_{\text{T}}(\tau) <$ 100 GeV) of the single-tau channel for pair production of up-type leptoquarks $\text{LQ}_{3}^{\text{u}}$.

Efficiency of the first bin of the multi-bin signal region (50 GeV $< p_{\text{T}}(\tau) <$ 100 GeV) of the single-tau channel for pair production of up-type leptoquarks $\text{LQ}_{3}^{\text{u}}$. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{u}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.

Acceptance of the middle bin of the multi-bin signal region (100 GeV $< p_{\text{T}}(\tau) <$ 200 GeV) of the single-tau channel for pair production of up-type leptoquarks $\text{LQ}_{3}^{\text{u}}$.

Efficiency of the middle bin of the multi-bin signal region (100 GeV $< p_{\text{T}}(\tau) <$ 200 GeV) of the single-tau channel for pair production of up-type leptoquarks $\text{LQ}_{3}^{\text{u}}$. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{u}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.

Acceptance of the last bin of the multi-bin signal region (200 GeV $< p_{\text{T}}(\tau)$) of the single-tau channel for pair production of up-type leptoquarks $\text{LQ}_{3}^{\text{u}}$.

Efficiency of the last bin of the multi-bin signal region (200 GeV $< p_{\text{T}}(\tau)$) of the single-tau channel for pair production of up-type leptoquarks $\text{LQ}_{3}^{\text{u}}$. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{u}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.

Acceptance of the signal region of the di-tau channel for pair production of up-type leptoquarks $\text{LQ}_{3}^{\text{u}}$.

Efficiency of the signal region of the di-tau channel for pair production of up-type leptoquarks $\text{LQ}_{3}^{\text{u}}$. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{u}} \rightarrow b\tau)$ of 0 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.

Acceptance of the one-bin signal region of the single-tau channel for pair production of down-type leptoquarks $\text{LQ}_{3}^{\text{d}}$.

Efficiency of the one-bin signal region of the single-tau channel for pair production of down-type leptoquarks $\text{LQ}_{3}^{\text{d}}$. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{d}} \rightarrow t\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.

Acceptance of the first bin of the multi-bin signal region (50 GeV $< p_{\text{T}}(\tau) <$ 100 GeV) of the single-tau channel for pair production of down-type leptoquarks $\text{LQ}_{3}^{\text{d}}$.

Efficiency of the first bin of the multi-bin signal region (50 GeV $< p_{\text{T}}(\tau) <$ 100 GeV) of the single-tau channel for pair production of down-type leptoquarks $\text{LQ}_{3}^{\text{d}}$. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{d}} \rightarrow t\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.

Acceptance of the middle bin of the multi-bin signal region (100 GeV $< p_{\text{T}}(\tau) <$ 200 GeV) of the single-tau channel for pair production of down-type leptoquarks $\text{LQ}_{3}^{\text{d}}$.

Efficiency of the middle bin of the multi-bin signal region (100 GeV $< p_{\text{T}}(\tau) <$ 200 GeV) of the single-tau channel for pair production of down-type leptoquarks $\text{LQ}_{3}^{\text{d}}$. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{d}} \rightarrow t\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.

Acceptance of the last bin of the multi-bin signal region (200 GeV $< p_{\text{T}}(\tau)$) of the single-tau channel for pair production of down-type leptoquarks $\text{LQ}_{3}^{\text{d}}$.

Efficiency of the last bin of the multi-bin signal region (200 GeV $< p_{\text{T}}(\tau)$) of the single-tau channel for pair production of down-type leptoquarks $\text{LQ}_{3}^{\text{d}}$. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{d}} \rightarrow t\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.

Acceptance of the signal region of the di-tau channel for pair production of down-type leptoquarks $\text{LQ}_{3}^{\text{d}}$.

Efficiency of the signal region of the di-tau channel for pair production of down-type leptoquarks $\text{LQ}_{3}^{\text{d}}$. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{d}} \rightarrow t\tau)$ of 0 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.

Acceptance of the one-bin signal region of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ in the minimal-coupling scenario.

Efficiency of the one-bin signal region of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ in the minimal-coupling scenario. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.

Acceptance of the first bin of the multi-bin signal region (50 GeV $< p_{\text{T}}(\tau) <$ 100 GeV) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ in the minimal-coupling scenario.

Efficiency of the first bin of the multi-bin signal region (50 GeV $< p_{\text{T}}(\tau) <$ 100 GeV) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ in the minimal-coupling scenario. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.

Acceptance of the middle bin of the multi-bin signal region (100 GeV $< p_{\text{T}}(\tau) <$ 200 GeV) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ in the minimal-coupling scenario.

Efficiency of the middle bin of the multi-bin signal region (100 GeV $< p_{\text{T}}(\tau) <$ 200 GeV) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ in the minimal-coupling scenario. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.

Acceptance of the last bin of the multi-bin signal region (200 GeV $< p_{\text{T}}(\tau)$) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ in the minimal-coupling scenario.

Efficiency of the last bin of the multi-bin signal region (200 GeV $< p_{\text{T}}(\tau)$) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ in the minimal-coupling scenario. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.

Acceptance of the signal region of the di-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ in the minimal-coupling scenario.

Efficiency of the signal region of the di-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ in the minimal-coupling scenario. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ of 0 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.

Acceptance of the one-bin signal region of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ with additional gauge couplings.

Efficiency of the one-bin signal region of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ with additional gauge couplings. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.

Acceptance of the first bin of the multi-bin signal region (50 GeV $< p_{\text{T}}(\tau) <$ 100 GeV) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ with additional gauge couplings.

Efficiency of the first bin of the multi-bin signal region (50 GeV $< p_{\text{T}}(\tau) <$ 100 GeV) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ with additional gauge couplings. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.

Acceptance of the middle bin of the multi-bin signal region (100 GeV $< p_{\text{T}}(\tau) <$ 200 GeV) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ with additional gauge couplings.

Efficiency of the middle bin of the multi-bin signal region (100 GeV $< p_{\text{T}}(\tau) <$ 200 GeV) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ with additional gauge couplings. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.

Acceptance of the last bin of the multi-bin signal region (200 GeV $< p_{\text{T}}(\tau)$) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ with additional gauge couplings.

Efficiency of the last bin of the multi-bin signal region (200 GeV $< p_{\text{T}}(\tau)$) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ with additional gauge couplings. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.

Acceptance of the signal region of the di-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ with additional gauge couplings.

Efficiency of the signal region of the di-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ with additional gauge couplings. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ of 0 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.

Acceptance of the one-bin signal region of the single-tau channel for pair production of top squarks with decays via tau sleptons.

Efficiency of the one-bin signal region of the single-tau channel for pair production of top squarks with decays via tau sleptons.

Acceptance of the first bin of the multi-bin signal region (50 GeV $< p_{\text{T}}(\tau) <$ 100 GeV) of the single-tau channel for pair production of top squarks with decays via tau sleptons.

Efficiency of the first bin of the multi-bin signal region (50 GeV $< p_{\text{T}}(\tau) <$ 100 GeV) of the single-tau channel for pair production of top squarks with decays via tau sleptons.

Acceptance of the middle bin of the multi-bin signal region (100 GeV $< p_{\text{T}}(\tau) <$ 200 GeV) of the single-tau channel for pair production of top squarks with decays via tau sleptons.

Efficiency of the middle bin of the multi-bin signal region (100 GeV $< p_{\text{T}}(\tau) <$ 200 GeV) of the single-tau channel for pair production of top squarks with decays via tau sleptons.

Acceptance of the last bin of the multi-bin signal region (200 GeV $< p_{\text{T}}(\tau)$) of the single-tau channel for pair production of top squarks with decays via tau sleptons.

Efficiency of the last bin of the multi-bin signal region (200 GeV $< p_{\text{T}}(\tau)$) of the single-tau channel for pair production of top squarks with decays via tau sleptons.

Acceptance of the signal region of the di-tau channel for pair production of top squarks with decays via tau sleptons.

Efficiency of the signal region of the di-tau channel for pair production of top squarks with decays via tau sleptons.

Cutflow for the benchmark signal model $m(\tilde{t}_{1}) = 1350$ GeV, $m(\tilde{\tau}_{1}) = 1090$ GeV for the di-tau SR. The simulated sample contains 30,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the di-tau channel.

Cutflow for the benchmark signal model $m(\tilde{t}_{1}) = 1350$ GeV, $m(\tilde{\tau}_{1}) = 1090$ GeV for the single-tau one-bin SR. The simulated sample contains 30,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the single-tau channel.

Cutflow for the benchmark signal model $m(\tilde{t}_{1}) = 1350$ GeV, $m(\tilde{\tau}_{1}) = 1090$ GeV for the single-tau multi-bin SR. The simulated sample contains 30,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the single-tau channel.

Cutflow for the benchmark signal model $m(\text{LQ}_{3}^{\text{u}}) = 1.2$ TeV, $\beta = 0.5$ for the di-tau SR. The simulated sample contains 210,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the di-tau channel.

Cutflow for the benchmark signal model $m(\text{LQ}_{3}^{\text{u}}) = 1.2$ TeV, $\beta = 0.5$ for the single-tau one-bin SR. The simulated sample contains 210,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the single-tau channel.

Cutflow for the benchmark signal model $m(\text{LQ}_{3}^{\text{u}}) = 1.2$ TeV, $\beta = 0.5$ for the single-tau multi-bin SR. The simulated sample contains 210,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the single-tau channel.

Cutflow for the benchmark signal model $m(\text{LQ}_{3}^{\text{d}}) = 1.2$ TeV, $\beta = 0.5$ for the di-tau SR. The simulated sample contains 210,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the di-tau channel.

Cutflow for the benchmark signal model $m(\text{LQ}_{3}^{\text{d}}) = 1.2$ TeV, $\beta = 0.5$ for the single-tau one-bin SR. The simulated sample contains 210,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the single-tau channel.

Cutflow for the benchmark signal model $m(\text{LQ}_{3}^{\text{d}}) = 1.2$ TeV, $\beta = 0.5$ for the single-tau multi-bin SR. The simulated sample contains 210,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the single-tau channel.

Cutflow for the benchmark signal model $m(\text{LQ}_{3}^{\text{v}}) = 1.4$ TeV, $\beta = 0.5$ in the minimal-coupling scenario for the di-tau SR. The simulated sample contains 50,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the di-tau channel.

Cutflow for the benchmark signal model $m(\text{LQ}_{3}^{\text{v}}) = 1.4$ TeV, $\beta = 0.5$ in the minimal-coupling scenario for the single-tau one-bin SR. The simulated sample contains 50,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the single-tau channel.

Cutflow for the benchmark signal model $m(\text{LQ}_{3}^{\text{v}}) = 1.4$ TeV, $\beta = 0.5$ in the minimal-coupling scenario for the single-tau multi-bin SR. The simulated sample contains 50,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the single-tau channel.

Cutflow for the benchmark signal model $m(\text{LQ}_{3}^{\text{v}}) = 1.4$ TeV, $\beta = 0.5$ in the Yang--Mills scenario for the di-tau SR. The simulated sample contains 50,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the di-tau channel.

Cutflow for the benchmark signal model $m(\text{LQ}_{3}^{\text{v}}) = 1.4$ TeV, $\beta = 0.5$ in the Yang--Mills scenario for the single-tau one-bin SR. The simulated sample contains 50,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the single-tau channel.

Cutflow for the benchmark signal model $m(\text{LQ}_{3}^{\text{v}}) = 1.4$ TeV, $\beta = 0.5$ in the Yang--Mills scenario for the single-tau multi-bin SR. The simulated sample contains 50,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the single-tau channel.

The rejection factor (inverse of the efficiency) for jets that have the other origins (background jets) are shown. The background jet rejection factor is calculated using pre-selected large-$R$ jets in the sample of simulated $Z\rightarrow\nu\nu$ + jets events, dominated by initial state radiation (ISR) jets. The efficiency correction factors are applied on the background rejection for the $W_{qq}$/$Z_{qq}$-tagging. The systematic uncertainty is represented by the hashed bands.

The boson-tagging efficiency for jets arising from $Z/h$ bosons decaying into $b\bar{b}$ (signal jets). The signal jet efficiency of $Z_{bb}$/$h_{bb}$-tagging is evaluated using a sample of pre-selected large-$R$ jets ($p_{\textrm{T}}>200~\textrm{GeV}, |\eta|<2.0, m_{J} > 40~\textrm{GeV}$) in the simulated $(\tilde{W},\tilde{B})$ simplified model signal events with $\Delta m(\tilde{\chi}_{\textrm{heavy}},~\tilde{\chi}_{\textrm{light}}) \ge 400~\textrm{GeV}$. The jets are matched with generator-level $Z/h$-bosons by $\Delta R<1.0$ which decay into $b\bar{b}$. The systematic uncertainty is represented by the hashed bands.

The rejection factor (inverse of the efficiency) for jets that have the other origins (background jets) are shown. The background jet rejection factor is calculated using pre-selected large-$R$ jets in the sample of simulated $Z\rightarrow\nu\nu$ + jets events, dominated by initial state radiation (ISR) jets. As for the $Z_{bb}$/$h_{bb}$-tagging, the rejection is shown as the function of number of $b$- or $c$-quarks contained in the large-$R$ jet within $\Delta R<1.0$. The systematic uncertainty is represented by the hashed bands.

The signal jet efficiency and background jet rejection for the $W_{qq}$-/$Z_{qq}$-tagging working point used in the analysis in comparison with those for the nominal working points (''50% efficiency W/Z tagger'' in ATL-PHYS-PUB-2020-017). The definition of the efficiency and rejection follow the caption of Figure 4. Note that the efficiency for the nominal working point is not 50% since they are tuned using jet samples with different pre-selection.

The signal jet efficiency and background jet rejection for the $W_{qq}$-/$Z_{qq}$-tagging working point used in the analysis in comparison with those for the nominal working points (''50% efficiency W/Z tagger'' in ATL-PHYS-PUB-2020-017). The definition of the efficiency and rejection follow the caption of Figure 4. Note that the efficiency for the nominal working point is not 50% since they are tuned using jet samples with different pre-selection.

The signal jet efficiency and background jet rejection for the $W_{qq}$-/$Z_{qq}$-tagging working point used in the analysis in comparison with those for the nominal working points (''50% efficiency W/Z tagger'' in ATL-PHYS-PUB-2020-017). The definition of the efficiency and rejection follow the caption of Figure 4. Note that the efficiency for the nominal working point is not 50% since they are tuned using jet samples with different pre-selection.

The signal jet efficiency and background jet rejection for the $W_{qq}$-/$Z_{qq}$-tagging working point used in the analysis in comparison with those for the nominal working points (''50% efficiency W/Z tagger'' in ATL-PHYS-PUB-2020-017). The definition of the efficiency and rejection follow the caption of Figure 4. Note that the efficiency for the nominal working point is not 50% since they are tuned using jet samples with different pre-selection.

The total post-fit uncertainty in each of the SRs and VRs.

Summary of the observed data and predicted SM background in all SRs. The background prediction in SR-4Q (SR-2B2Q) is obtained by a background-only fit to CR0L-4Q (CR0L-2B2Q). The total systematic uncertainty on the background prediction is shown by the hatched area. Distributions of a few representative signals are overlaid. A few representative signals are overlaid. For the $(\tilde{W},\tilde{B})$ simplified model models, the label $(x,y)$ indicates $(m(\tilde{\chi}_{1}^{\pm}), m(\tilde{\chi}_{1}^{0}))=(x,y)~\textrm{GeV}$. The bottom panel shows the statistical significance of the discrepancy between the observed number of events and the SM expectation.

Number of observed data events and the SM backgrounds in the SRs and the CR0L bins. The SM backgrounds are predicted by the background-only fits. Note that the relative uncertainty on the expected yield in the CRs between the reducible backgrounds are identical, given that a common normalization factor is assigned for all of them in the fit. Yields for negligible backgrounds are indicated by "0.0000001±0.0000001" in the table.

Number of observed data events and the post-fit SM background prediction in the VR1L(1Y) bins and the corresponding CR1L(1Y) bins. "-" indicates negligibly small contribution. Note that the relative uncertainty on the expected yield in the CRs between the reducible backgrounds are identical, given that a common normalization factor is assigned for all of them in the fit. Yields for negligible backgrounds are indicated by "0.0000001±0.0000001" in the table.

$m_{\textrm{eff}}$ distribution in SR-4Q-VV. The post-fit SM background expectation using the background-only fit is shown in a histogram stack. Distributions of a few representative signals are overlaid. The bottom panels show the ratio of the observed data to the background prediction. The selection criteria on the variable shown by each plot is removed, while the arrow indicates the cut value to define the region. A few representative signals are overlaid. For the $(\tilde{W},\tilde{B})$ simplified model models, the label $(x,y)$ indicates $(m(\tilde{\chi}_{1}^{\pm}), m(\tilde{\chi}_{1}^{0}))=(x,y)~\text{GeV}$.

Distribution of $m(J_{1})$ in SR-4Q-VV. The post-fit SM background expectation using the background-only fit is shown in a histogram stack. Distributions of relevant signals are overlaid. The bottom panels show the ratio of the observed data to the background prediction. The selection criteria on the variable shown by each plot is removed, while the arrow indicates the cut value to define the region. A few representative signals are overlaid. For the $(\tilde{W},\tilde{B})$ simplified model models, the label $(x,y)$ indicates $(m(\tilde{\chi}_{1}^{\pm}), m(\tilde{\chi}_{1}^{0}))=(x,y)~\text{GeV}$.

Distribution of $D_2(J_{1})$ in SR-4Q-VV. For $D_2$, the cut value applied for $V_{qq}$-tagging ($D_{2,\text{cut}}$) is subtracted as the off-set so that $D_2-D_{2,\text{cut}}(J)<0$ represents $J$ passing the $D_2$ selection. The post-fit SM background expectation using the background-only fit is shown in a histogram stack. Distributions of relevant signals are overlaid. The bottom panels show the ratio of the observed data to the background prediction. The selection criteria on the variable shown by each plot is removed, while the arrow indicates the cut value to define the region. A few representative signals are overlaid. For the $(\tilde{W},\tilde{B})$ simplified model models, the label $(x,y)$ indicates $(m(\tilde{\chi}_{1}^{\pm}), m(\tilde{\chi}_{1}^{0}))=(x,y)~\text{GeV}$.

Distribution of $m(J_{2})$ in SR-4Q-VV. The post-fit SM background expectation using the background-only fit is shown in a histogram stack. Distributions of relevant signals are overlaid. The bottom panels show the ratio of the observed data to the background prediction. The selection criteria on the variable shown by each plot is removed, while the arrow indicates the cut value to define the region. A few representative signals are overlaid. For the $(\tilde{W},\tilde{B})$ simplified model models, the label $(x,y)$ indicates $(m(\tilde{\chi}_{1}^{\pm}), m(\tilde{\chi}_{1}^{0}))=(x,y)~\text{GeV}$.

Distribution of $D_2(J_{2})$ in SR-4Q-VV. For $D_2$, the cut value applied for $V_{qq}$-tagging ($D_{2,\text{cut}}$) is subtracted as the off-set so that $D_2-D_{2,\text{cut}}(J)<0$ represents $J$ passing the $D_2$ selection. The post-fit SM background expectation using the background-only fit is shown in a histogram stack. Distributions of relevant signals are overlaid. The bottom panels show the ratio of the observed data to the background prediction. The selection criteria on the variable shown by each plot is removed, while the arrow indicates the cut value to define the region. A few representative signals are overlaid. For the $(\tilde{W},\tilde{B})$ simplified model models, the label $(x,y)$ indicates $(m(\tilde{\chi}_{1}^{\pm}), m(\tilde{\chi}_{1}^{0}))=(x,y)~\text{GeV}$.

$m_{\textrm{T2}}$ distributions in SR-2B2Q-VZ. The post-fit SM background expectation using the background-only fit is shown in a histogram stack. Distributions of a few representative signals are overlaid. The bottom panels show the ratio of the observed data to the background prediction. The selection criteria on the variable shown by each plot is removed, while the arrow indicates the cut value to define the region. A few representative signals are overlaid. For the $(\tilde{W},\tilde{B})$ simplified model models, the label $(x,y)$ indicates $(m(\tilde{\chi}_{1}^{\pm}), m(\tilde{\chi}_{1}^{0}))=(x,y)~\text{GeV}$.

Distribution of $m(J_{bb})$ in SR-2B2Q-VZ. The post-fit SM background expectation using the background-only fit is shown in a histogram stack. Distributions of relevant signals are overlaid. The bottom panels show the ratio of the observed data to the background prediction. The selection criteria on the variable shown by each plot is removed, while the arrow indicates the cut value to define the region. A few representative signals are overlaid. For the $(\tilde{W},\tilde{B})$ simplified model models, the label $(x,y)$ indicates $(m(\tilde{\chi}_{1}^{\pm}), m(\tilde{\chi}_{1}^{0}))=(x,y)~\text{GeV}$.

Distribution of $m_{\textrm{eff}} $ in SR-2B2Q-VZ. The post-fit SM background expectation using the background-only fit is shown in a histogram stack. Distributions of relevant signals are overlaid. The bottom panels show the ratio of the observed data to the background prediction. The selection criteria on the variable shown by each plot is removed, while the arrow indicates the cut value to define the region. A few representative signals are overlaid. For the $(\tilde{W},\tilde{B})$ simplified model models, the label $(x,y)$ indicates $(m(\tilde{\chi}_{1}^{\pm}), m(\tilde{\chi}_{1}^{0}))=(x,y)~\text{GeV}$.

$m_{\textrm{T2}}$ distributions in SR-2B2Q-Vh. The post-fit SM background expectation using the background-only fit is shown in a histogram stack. Distributions of a few representative signals are overlaid. The bottom panels show the ratio of the observed data to the background prediction. The selection criteria on the variable shown by each plot is removed, while the arrow indicates the cut value to define the region. A few representative signals are overlaid. For the $(\tilde{W},\tilde{B})$ simplified model models, the label $(x,y)$ indicates $(m(\tilde{\chi}_{1}^{\pm}), m(\tilde{\chi}_{1}^{0}))=(x,y)~\text{GeV}$.

Distribution of $m(J_{bb})$ in SR-2B2Q-Vh. The post-fit SM background expectation using the background-only fit is shown in a histogram stack. Distributions of relevant signals are overlaid. The bottom panels show the ratio of the observed data to the background prediction. The selection criteria on the variable shown by each plot is removed, while the arrow indicates the cut value to define the region. A few representative signals are overlaid. For the $(\tilde{W},\tilde{B})$ simplified model models, the label $(x,y)$ indicates $(m(\tilde{\chi}_{1}^{\pm}), m(\tilde{\chi}_{1}^{0}))=(x,y)~\text{GeV}$.

Distribution of $m_{\textrm{eff}} $ in SR-2B2Q-Vh. The post-fit SM background expectation using the background-only fit is shown in a histogram stack. Distributions of relevant signals are overlaid. The bottom panels show the ratio of the observed data to the background prediction. The selection criteria on the variable shown by each plot is removed, while the arrow indicates the cut value to define the region. A few representative signals are overlaid. For the $(\tilde{W},\tilde{B})$ simplified model models, the label $(x,y)$ indicates $(m(\tilde{\chi}_{1}^{\pm}), m(\tilde{\chi}_{1}^{0}))=(x,y)~\text{GeV}$.

Exclusion limits for $(\tilde{W},\tilde{B})$ simplifiec model as a function of the produced wino mass ($m(\tilde{\chi}_{1}^{\pm}/\tilde{\chi}_{2}^{0})$) and the bino LSP mass ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed) and observed (solid) 95% CL exclusion limits on $(\tilde{W},\tilde{B})$ simplified models; C1C1-WW. The expected limit for the 1$\sigma$ down variation is not shown as no mass points could be excluded.

Exclusion limits for $(\tilde{W},\tilde{B})$ simplifiec model as a function of the produced wino mass ($m(\tilde{\chi}_{1}^{\pm}/\tilde{\chi}_{2}^{0})$) and the bino LSP mass ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed) and observed (solid) 95% CL exclusion limits on $(\tilde{W},\tilde{B})$ simplified models; C1C1-WW. The expected limit for the 1$\sigma$ down variation is not shown as no mass points could be excluded.

Exclusion limits for $(\tilde{W},\tilde{B})$ simplifiec model as a function of the produced wino mass ($m(\tilde{\chi}_{1}^{\pm}/\tilde{\chi}_{2}^{0})$) and the bino LSP mass ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed) and observed (solid) 95% CL exclusion limits on $(\tilde{W},\tilde{B})$ simplified models; C1C1-WW. The expected limit for the 1$\sigma$ down variation is not shown as no mass points could be excluded.

Exclusion limits for $(\tilde{W},\tilde{B})$ simplifiec model as a function of the produced wino mass ($m(\tilde{\chi}_{1}^{\pm}/\tilde{\chi}_{2}^{0})$) and the bino LSP mass ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed) and observed (solid) 95% CL exclusion limits on $(\tilde{W},\tilde{B})$ simplified models; C1C1-WW. The expected limit for the 1$\sigma$ down variation is not shown as no mass points could be excluded.

Exclusion limits for $(\tilde{W},\tilde{B})$ simplifiec model as a function of the produced wino mass ($m(\tilde{\chi}_{1}^{\pm}/\tilde{\chi}_{2}^{0})$) and the bino LSP mass ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed) and observed (solid) 95% CL exclusion limits on $(\tilde{W},\tilde{B})$ simplified models; C1C1-WW. The expected limit for the 1$\sigma$ down variation is not shown as no mass points could be excluded.

Exclusion limits for $(\tilde{W},\tilde{B})$ simplifiec model as a function of the produced wino mass ($m(\tilde{\chi}_{1}^{\pm}/\tilde{\chi}_{2}^{0})$) and the bino LSP mass ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed) and observed (solid) 95% CL exclusion limits on $(\tilde{W},\tilde{B})$ simplified models; C1N2-WZ.

Exclusion limits for $(\tilde{W},\tilde{B})$ simplifiec model as a function of the produced wino mass ($m(\tilde{\chi}_{1}^{\pm}/\tilde{\chi}_{2}^{0})$) and the bino LSP mass ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed) and observed (solid) 95% CL exclusion limits on $(\tilde{W},\tilde{B})$ simplified models; C1N2-WZ.

Exclusion limits for $(\tilde{W},\tilde{B})$ simplifiec model as a function of the produced wino mass ($m(\tilde{\chi}_{1}^{\pm}/\tilde{\chi}_{2}^{0})$) and the bino LSP mass ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed) and observed (solid) 95% CL exclusion limits on $(\tilde{W},\tilde{B})$ simplified models; C1N2-WZ.

Exclusion limits for $(\tilde{W},\tilde{B})$ simplifiec model as a function of the produced wino mass ($m(\tilde{\chi}_{1}^{\pm}/\tilde{\chi}_{2}^{0})$) and the bino LSP mass ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed) and observed (solid) 95% CL exclusion limits on $(\tilde{W},\tilde{B})$ simplified models; C1N2-WZ.

Exclusion limits for $(\tilde{W},\tilde{B})$ simplifiec model as a function of the produced wino mass ($m(\tilde{\chi}_{1}^{\pm}/\tilde{\chi}_{2}^{0})$) and the bino LSP mass ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed) and observed (solid) 95% CL exclusion limits on $(\tilde{W},\tilde{B})$ simplified models; C1N2-WZ.

Exclusion limits for $(\tilde{W},\tilde{B})$ simplifiec model as a function of the produced wino mass ($m(\tilde{\chi}_{1}^{\pm}/\tilde{\chi}_{2}^{0})$) and the bino LSP mass ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed) and observed (solid) 95% CL exclusion limits on $(\tilde{W},\tilde{B})$ simplified models; C1N2-WZ.

Exclusion limits for $(\tilde{W},\tilde{B})$ simplifiec model as a function of the produced wino mass ($m(\tilde{\chi}_{1}^{\pm}/\tilde{\chi}_{2}^{0})$) and the bino LSP mass ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed) and observed (solid) 95% CL exclusion limits on $(\tilde{W},\tilde{B})$ simplified models; C1N2-Wh.

Exclusion limits for $(\tilde{W},\tilde{B})$ simplifiec model as a function of the produced wino mass ($m(\tilde{\chi}_{1}^{\pm}/\tilde{\chi}_{2}^{0})$) and the bino LSP mass ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed) and observed (solid) 95% CL exclusion limits on $(\tilde{W},\tilde{B})$ simplified models; C1N2-Wh.

Exclusion limits for $(\tilde{W},\tilde{B})$ simplifiec model as a function of the produced wino mass ($m(\tilde{\chi}_{1}^{\pm}/\tilde{\chi}_{2}^{0})$) and the bino LSP mass ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed) and observed (solid) 95% CL exclusion limits on $(\tilde{W},\tilde{B})$ simplified models; C1N2-Wh.

Exclusion limits for $(\tilde{W},\tilde{B})$ simplifiec model as a function of the produced wino mass ($m(\tilde{\chi}_{1}^{\pm}/\tilde{\chi}_{2}^{0})$) and the bino LSP mass ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed) and observed (solid) 95% CL exclusion limits on $(\tilde{W},\tilde{B})$ simplified models; C1N2-Wh.

Exclusion limits for $(\tilde{W},\tilde{B})$ simplifiec model as a function of the produced wino mass ($m(\tilde{\chi}_{1}^{\pm}/\tilde{\chi}_{2}^{0})$) and the bino LSP mass ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed) and observed (solid) 95% CL exclusion limits on $(\tilde{W},\tilde{B})$ simplified models; C1N2-Wh.

Exclusion limits for $(\tilde{W},\tilde{B})$ simplifiec model as a function of the produced wino mass ($m(\tilde{\chi}_{1}^{\pm}/\tilde{\chi}_{2}^{0})$) and the bino LSP mass ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed) and observed (solid) 95% CL exclusion limits on $(\tilde{W},\tilde{B})$ simplified models; C1N2-Wh.

Exclusion limits for the $(\tilde{W},\tilde{B})$ and $(\tilde{H},\tilde{B})$ models shown as a function of the mass of wino/higgsino chargino ($m(\tilde{\chi}_{1}^{\pm})$) and the mass of bino LSP ($m(\tilde{\chi}_{1}^{0})$). Expected limits for various $\mathcal{B}(\tilde{\chi}_{2}^{0} \rightarrow Z \tilde{\chi}_{1}^{0})$ hypotheses overlaid. The outer and inner bundles correspond to the limits for the $(\tilde{W},\tilde{B})$ and $(\tilde{H},\tilde{B})$ models respectively.

Exclusion limits for the $(\tilde{W},\tilde{B})$ and $(\tilde{H},\tilde{B})$ models shown as a function of the mass of wino/higgsino chargino ($m(\tilde{\chi}_{1}^{\pm})$) and the mass of bino LSP ($m(\tilde{\chi}_{1}^{0})$). Observed limits for various $\mathcal{B}(\tilde{\chi}_{2}^{0} \rightarrow Z \tilde{\chi}_{1}^{0})$ hypotheses overlaid. The outer and inner bundles correspond to the limits for the $(\tilde{W},\tilde{B})$ and $(\tilde{H},\tilde{B})$ models respectively.

Exclusion limits for the $(\tilde{W},\tilde{B})$ and $(\tilde{H},\tilde{B})$ models shown as a function of the mass of wino/higgsino chargino ($m(\tilde{\chi}_{1}^{\pm})$) and the mass of bino LSP ($m(\tilde{\chi}_{1}^{0})$). Expected limits for various $\mathcal{B}(\tilde{\chi}_{2}^{0} \rightarrow Z \tilde{\chi}_{1}^{0})$ hypotheses overlaid. The outer and inner bundles correspond to the limits for the $(\tilde{W},\tilde{B})$ and $(\tilde{H},\tilde{B})$ models respectively.

Exclusion limits for the $(\tilde{W},\tilde{B})$ and $(\tilde{H},\tilde{B})$ models shown as a function of the mass of wino/higgsino chargino ($m(\tilde{\chi}_{1}^{\pm})$) and the mass of bino LSP ($m(\tilde{\chi}_{1}^{0})$). Observed limits for various $\mathcal{B}(\tilde{\chi}_{2}^{0} \rightarrow Z \tilde{\chi}_{1}^{0})$ hypotheses overlaid. The outer and inner bundles correspond to the limits for the $(\tilde{W},\tilde{B})$ and $(\tilde{H},\tilde{B})$ models respectively.

Exclusion limits for the $(\tilde{W},\tilde{B})$ and $(\tilde{H},\tilde{B})$ models shown as a function of the mass of wino/higgsino chargino ($m(\tilde{\chi}_{1}^{\pm})$) and the mass of bino LSP ($m(\tilde{\chi}_{1}^{0})$). Expected limits for various $\mathcal{B}(\tilde{\chi}_{2}^{0} \rightarrow Z \tilde{\chi}_{1}^{0})$ hypotheses overlaid. The outer and inner bundles correspond to the limits for the $(\tilde{W},\tilde{B})$ and $(\tilde{H},\tilde{B})$ models respectively.

Exclusion limits for the $(\tilde{W},\tilde{B})$ models shown as a function of the mass of wino/higgsino chargino ($m(\tilde{\chi}_{1}^{\pm})$) and the mass of bino LSP ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed) and observed (solid red) 95% CL exclusion limits for a representative branching ratio $\mathcal{B}(\tilde{\chi}_{2}^{0} \rightarrow Z\tilde{\chi}_{1}^{0})=50$%.

Exclusion limits for the $(\tilde{W},\tilde{B})$ models shown as a function of the mass of wino/higgsino chargino ($m(\tilde{\chi}_{1}^{\pm})$) and the mass of bino LSP ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed) and observed (solid red) 95% CL exclusion limits for a representative branching ratio $\mathcal{B}(\tilde{\chi}_{2}^{0} \rightarrow Z\tilde{\chi}_{1}^{0})=50$%.

Exclusion limits for the $(\tilde{W},\tilde{B})$ and $(\tilde{H},\tilde{B})$ models shown as a function of the mass of wino/higgsino chargino ($m(\tilde{\chi}_{1}^{\pm})$) and the mass of bino LSP ($m(\tilde{\chi}_{1}^{0})$). Observed limits for various $\mathcal{B}(\tilde{\chi}_{2}^{0} \rightarrow Z \tilde{\chi}_{1}^{0})$ hypotheses overlaid. The outer and inner bundles correspond to the limits for the $(\tilde{W},\tilde{B})$ and $(\tilde{H},\tilde{B})$ models respectively.

Exclusion limits for the $(\tilde{W},\tilde{B})$ models shown as a function of the mass of wino/higgsino chargino ($m(\tilde{\chi}_{1}^{\pm})$) and the mass of bino LSP ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed) and observed (solid red) 95% CL exclusion limits for a representative branching ratio $\mathcal{B}(\tilde{\chi}_{2}^{0} \rightarrow Z\tilde{\chi}_{1}^{0})=50$%.

Exclusion limits for the $(\tilde{W},\tilde{B})$ models shown as a function of the mass of wino/higgsino chargino ($m(\tilde{\chi}_{1}^{\pm})$) and the mass of bino LSP ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed) and observed (solid red) 95% CL exclusion limits for a representative branching ratio $\mathcal{B}(\tilde{\chi}_{2}^{0} \rightarrow Z\tilde{\chi}_{1}^{0})=50$%.

Exclusion limits for the $(\tilde{W},\tilde{B})$ and $(\tilde{H},\tilde{B})$ models shown as a function of the mass of wino/higgsino chargino ($m(\tilde{\chi}_{1}^{\pm})$) and the mass of bino LSP ($m(\tilde{\chi}_{1}^{0})$). Expected limits for various $\mathcal{B}(\tilde{\chi}_{2}^{0} \rightarrow Z \tilde{\chi}_{1}^{0})$ hypotheses overlaid. The outer and inner bundles correspond to the limits for the $(\tilde{W},\tilde{B})$ and $(\tilde{H},\tilde{B})$ models respectively.

Exclusion limits for the $(\tilde{W},\tilde{B})$ and $(\tilde{H},\tilde{B})$ models shown as a function of the mass of wino/higgsino chargino ($m(\tilde{\chi}_{1}^{\pm})$) and the mass of bino LSP ($m(\tilde{\chi}_{1}^{0})$). Observed limits for various $\mathcal{B}(\tilde{\chi}_{2}^{0} \rightarrow Z \tilde{\chi}_{1}^{0})$ hypotheses overlaid. The outer and inner bundles correspond to the limits for the $(\tilde{W},\tilde{B})$ and $(\tilde{H},\tilde{B})$ models respectively.

Exclusion limits for the $(\tilde{W},\tilde{B})$ and $(\tilde{H},\tilde{B})$ models shown as a function of the mass of wino/higgsino chargino ($m(\tilde{\chi}_{1}^{\pm})$) and the mass of bino LSP ($m(\tilde{\chi}_{1}^{0})$). Expected limits for various $\mathcal{B}(\tilde{\chi}_{2}^{0} \rightarrow Z \tilde{\chi}_{1}^{0})$ hypotheses overlaid. The outer and inner bundles correspond to the limits for the $(\tilde{W},\tilde{B})$ and $(\tilde{H},\tilde{B})$ models respectively.

Exclusion limits for the $(\tilde{W},\tilde{B})$ and $(\tilde{H},\tilde{B})$ models shown as a function of the mass of wino/higgsino chargino ($m(\tilde{\chi}_{1}^{\pm})$) and the mass of bino LSP ($m(\tilde{\chi}_{1}^{0})$). Observed limits for various $\mathcal{B}(\tilde{\chi}_{2}^{0} \rightarrow Z \tilde{\chi}_{1}^{0})$ hypotheses overlaid. The outer and inner bundles correspond to the limits for the $(\tilde{W},\tilde{B})$ and $(\tilde{H},\tilde{B})$ models respectively.

Exclusion limits for the $(\tilde{W},\tilde{B})$ and $(\tilde{H},\tilde{B})$ models shown as a function of the mass of wino/higgsino chargino ($m(\tilde{\chi}_{1}^{\pm})$) and the mass of bino LSP ($m(\tilde{\chi}_{1}^{0})$). Expected limits for various $\mathcal{B}(\tilde{\chi}_{2}^{0} \rightarrow Z \tilde{\chi}_{1}^{0})$ hypotheses overlaid. The outer and inner bundles correspond to the limits for the $(\tilde{W},\tilde{B})$ and $(\tilde{H},\tilde{B})$ models respectively. The expected limit for the 1$\sigma$ down variation is not shown as no mass points could be excluded.

Exclusion limits for the $(\tilde{H},\tilde{B})$ models shown as a function of the mass of wino/higgsino chargino ($m(\tilde{\chi}_{1}^{\pm})$) and the mass of bino LSP ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed) and observed (solid red) 95% CL exclusion limits for a representative branching ratio $\mathcal{B}(\tilde{\chi}_{2}^{0} \rightarrow Z\tilde{\chi}_{1}^{0})=50$%. The expected limit for the 1$\sigma$ down variation is not shown as no mass points could be excluded.

Exclusion limits for the $(\tilde{W},\tilde{B})$ and $(\tilde{H},\tilde{B})$ models shown as a function of the mass of wino/higgsino chargino ($m(\tilde{\chi}_{1}^{\pm})$) and the mass of bino LSP ($m(\tilde{\chi}_{1}^{0})$). Observed limits for various $\mathcal{B}(\tilde{\chi}_{2}^{0} \rightarrow Z \tilde{\chi}_{1}^{0})$ hypotheses overlaid. The outer and inner bundles correspond to the limits for the $(\tilde{W},\tilde{B})$ and $(\tilde{H},\tilde{B})$ models respectively. The expected limit for the 1$\sigma$ down variation is not shown as no mass points could be excluded.

Exclusion limits for the $(\tilde{H},\tilde{B})$ models shown as a function of the mass of wino/higgsino chargino ($m(\tilde{\chi}_{1}^{\pm})$) and the mass of bino LSP ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed) and observed (solid red) 95% CL exclusion limits for a representative branching ratio $\mathcal{B}(\tilde{\chi}_{2}^{0} \rightarrow Z\tilde{\chi}_{1}^{0})=50$%. The expected limit for the 1$\sigma$ down variation is not shown as no mass points could be excluded.

Exclusion limits for the $(\tilde{H},\tilde{B})$ models shown as a function of the mass of wino/higgsino chargino ($m(\tilde{\chi}_{1}^{\pm})$) and the mass of bino LSP ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed) and observed (solid red) 95% CL exclusion limits for a representative branching ratio $\mathcal{B}(\tilde{\chi}_{2}^{0} \rightarrow Z\tilde{\chi}_{1}^{0})=50$%. The expected limit for the 1$\sigma$ down variation is not shown as no mass points could be excluded.

95% CL exclusion limits for the $(\tilde{W},\tilde{H})$ models. The limits are projected on to a two-dimensional plane of the physical electroweakino masses $(m(\tilde{\chi}_{2}^{\pm}),m(\tilde{\chi}_{1}^{0}))$ representing $(m(\tilde{\chi}_{\textrm{heavy}}),m(\tilde{\chi}_{\textrm{light}}))$.

95% CL exclusion limits for the $(\tilde{W},\tilde{H})$ models. The limits are projected on to a two-dimensional plane of the physical electroweakino masses $(m(\tilde{\chi}_{2}^{\pm}),m(\tilde{\chi}_{1}^{0}))$ representing $(m(\tilde{\chi}_{\textrm{heavy}}),m(\tilde{\chi}_{\textrm{light}}))$.

95% CL exclusion limits for the $(\tilde{W},\tilde{H})$ models. The limits are projected on to a two-dimensional plane of the physical electroweakino masses $(m(\tilde{\chi}_{2}^{\pm}),m(\tilde{\chi}_{1}^{0}))$ representing $(m(\tilde{\chi}_{\textrm{heavy}}),m(\tilde{\chi}_{\textrm{light}}))$.

95% CL exclusion limits for the $(\tilde{W},\tilde{H})$ models. The limits are projected on to a two-dimensional plane of the physical electroweakino masses $(m(\tilde{\chi}_{2}^{\pm}),m(\tilde{\chi}_{1}^{0}))$ representing $(m(\tilde{\chi}_{\textrm{heavy}}),m(\tilde{\chi}_{\textrm{light}}))$.

95% CL exclusion limits for the $(\tilde{W},\tilde{H})$ models. The limits are projected on to a two-dimensional plane of the physical electroweakino masses $(m(\tilde{\chi}_{2}^{\pm}),m(\tilde{\chi}_{1}^{0}))$ representing $(m(\tilde{\chi}_{\textrm{heavy}}),m(\tilde{\chi}_{\textrm{light}}))$.

95% CL exclusion limits for the $(\tilde{W},\tilde{H})$ models. The limits are projected on to a two-dimensional plane of the physical electroweakino masses $(m(\tilde{\chi}_{2}^{\pm}),m(\tilde{\chi}_{1}^{0}))$ representing $(m(\tilde{\chi}_{\textrm{heavy}}),m(\tilde{\chi}_{\textrm{light}}))$.

95% CL exclusion limits for the $(\tilde{H},\tilde{W})$ models. The limits are projected on to a two-dimensional plane of the physical electroweakino masses $(m(\tilde{\chi}_{2}^{\pm}),m(\tilde{\chi}_{1}^{0}))$ representing $(m(\tilde{\chi}_{\textrm{heavy}}),m(\tilde{\chi}_{\textrm{light}}))$. The expected limit for the 1$\sigma$ down variation is not shown as no mass points could be excluded.

95% CL exclusion limits for the $(\tilde{H},\tilde{W})$ models. The limits are projected on to a two-dimensional plane of the physical electroweakino masses $(m(\tilde{\chi}_{2}^{\pm}),m(\tilde{\chi}_{1}^{0}))$ representing $(m(\tilde{\chi}_{\textrm{heavy}}),m(\tilde{\chi}_{\textrm{light}}))$. The expected limit for the 1$\sigma$ down variation is not shown as no mass points could be excluded.

95% CL exclusion limits for the $(\tilde{H},\tilde{W})$ models. The limits are projected on to a two-dimensional plane of the physical electroweakino masses $(m(\tilde{\chi}_{2}^{\pm}),m(\tilde{\chi}_{1}^{0}))$ representing $(m(\tilde{\chi}_{\textrm{heavy}}),m(\tilde{\chi}_{\textrm{light}}))$. The expected limit for the 1$\sigma$ down variation is not shown as no mass points could be excluded.

95% CL exclusion limits for the $(\tilde{H},\tilde{W})$ models. The limits are projected on to a two-dimensional plane of the physical electroweakino masses $(m(\tilde{\chi}_{2}^{\pm}),m(\tilde{\chi}_{1}^{0}))$ representing $(m(\tilde{\chi}_{\textrm{heavy}}),m(\tilde{\chi}_{\textrm{light}}))$. The expected limit for the 1$\sigma$ down variation is not shown as no mass points could be excluded.

95% CL exclusion limits for the $(\tilde{H},\tilde{W})$ models. The limits are projected on to a two-dimensional plane of the physical electroweakino masses $(m(\tilde{\chi}_{2}^{\pm}),m(\tilde{\chi}_{1}^{0}))$ representing $(m(\tilde{\chi}_{\textrm{heavy}}),m(\tilde{\chi}_{\textrm{light}}))$. The expected limit for the 1$\sigma$ down variation is not shown as no mass points could be excluded.

95% CL exclusion limits for the $(\tilde{W},\tilde{H})$ models. The limits are projected on to a two-dimensional plane as a function of the wino/higgsino mass parameters: $(M_2,\mu)$. For the limits shown on the $(M_2,\mu)$ plane, the excluded regions are indicated by the area inside the contours. The round excluded area in the top part corresponds to the excluded parameter space in the $(\tilde{W},~\tilde{H})$ model $(M_{2} > |\mu|)$, while the two small areas in at the bottom are that in the $(\tilde{H},~\tilde{W})$ model $(M_{2} < |\mu|)$.

95% CL exclusion limits for the $(\tilde{W},\tilde{H})$ models. The limits are projected on to a two-dimensional plane as a function of the wino/higgsino mass parameters: $(M_2,\mu)$. For the limits shown on the $(M_2,\mu)$ plane, the excluded regions are indicated by the area inside the contours. The expected limits for the 1$\sigma$ down variation are not shown as no mass points could be excluded. The round excluded area in the top part corresponds to the excluded parameter space in the $(\tilde{W},~\tilde{H})$ model $(M_{2} > |\mu|)$, while the two small areas in at the bottom are that in the $(\tilde{H},~\tilde{W})$ model $(M_{2} < |\mu|)$.

95% CL exclusion limits for the $(\tilde{W},\tilde{H})$ models. The limits are projected on to a two-dimensional plane as a function of the wino/higgsino mass parameters: $(M_2,\mu)$. For the limits shown on the $(M_2,\mu)$ plane, the excluded regions are indicated by the area inside the contours. The expected limits for the 1$\sigma$ down variation are not shown as no mass points could be excluded. The round excluded area in the top part corresponds to the excluded parameter space in the $(\tilde{W},~\tilde{H})$ model $(M_{2} > |\mu|)$, while the two small areas in at the bottom are that in the $(\tilde{H},~\tilde{W})$ model $(M_{2} < |\mu|)$.

95% CL exclusion limits for the $(\tilde{W},\tilde{H})$ models. The limits are projected on to a two-dimensional plane as a function of the wino/higgsino mass parameters: $(M_2,\mu)$. For the limits shown on the $(M_2,\mu)$ plane, the excluded regions are indicated by the area inside the contours. The round excluded area in the top part corresponds to the excluded parameter space in the $(\tilde{W},~\tilde{H})$ model $(M_{2} > |\mu|)$, while the two small areas in at the bottom are that in the $(\tilde{H},~\tilde{W})$ model $(M_{2} < |\mu|)$.

95% CL exclusion limits for the $(\tilde{W},\tilde{H})$ models. The limits are projected on to a two-dimensional plane as a function of the wino/higgsino mass parameters: $(M_2,\mu)$. For the limits shown on the $(M_2,\mu)$ plane, the excluded regions are indicated by the area inside the contours. The expected limits for the 1$\sigma$ down variation are not shown as no mass points could be excluded. The round excluded area in the top part corresponds to the excluded parameter space in the $(\tilde{W},~\tilde{H})$ model $(M_{2} > |\mu|)$, while the two small areas in at the bottom are that in the $(\tilde{H},~\tilde{W})$ model $(M_{2} < |\mu|)$.

95% CL exclusion limits for the $(\tilde{W},\tilde{H})$ models. The limits are projected on to a two-dimensional plane as a function of the wino/higgsino mass parameters: $(M_2,\mu)$. For the limits shown on the $(M_2,\mu)$ plane, the excluded regions are indicated by the area inside the contours. The expected limits for the 1$\sigma$ down variation are not shown as no mass points could be excluded. The round excluded area in the top part corresponds to the excluded parameter space in the $(\tilde{W},~\tilde{H})$ model $(M_{2} > |\mu|)$, while the two small areas in at the bottom are that in the $(\tilde{H},~\tilde{W})$ model $(M_{2} < |\mu|)$.

95% CL exclusion limits for the $(\tilde{H},\tilde{W})$ models. The limits are projected on to a two-dimensional plane as a function of the wino/higgsino mass parameters: $(M_2,\mu)$. For the limits shown on the $(M_2,\mu)$ plane, the excluded regions are indicated by the area inside the contours. The round excluded area in the top part corresponds to the excluded parameter space in the $(\tilde{W},~\tilde{H})$ model $(M_{2} > |\mu|)$, while the two small areas in at the bottom are that in the $(\tilde{H},~\tilde{W})$ model $(M_{2} < |\mu|)$.

95% CL exclusion limits for the $(\tilde{H},\tilde{W})$ models. The limits are projected on to a two-dimensional plane as a function of the wino/higgsino mass parameters: $(M_2,\mu)$. For the limits shown on the $(M_2,\mu)$ plane, the excluded regions are indicated by the area inside the contours. The expected limits for the 1$\sigma$ down variation are not shown as no mass points could be excluded. The round excluded area in the top part corresponds to the excluded parameter space in the $(\tilde{W},~\tilde{H})$ model $(M_{2} > |\mu|)$, while the two small areas in at the bottom are that in the $(\tilde{H},~\tilde{W})$ model $(M_{2} < |\mu|)$.

95% CL exclusion limits for the $(\tilde{H},\tilde{W})$ models. The limits are projected on to a two-dimensional plane as a function of the wino/higgsino mass parameters: $(M_2,\mu)$. For the limits shown on the $(M_2,\mu)$ plane, the excluded regions are indicated by the area inside the contours. The round excluded area in the top part corresponds to the excluded parameter space in the $(\tilde{W},~\tilde{H})$ model $(M_{2} > |\mu|)$, while the two small areas in at the bottom are that in the $(\tilde{H},~\tilde{W})$ model $(M_{2} < |\mu|)$.

95% CL exclusion limits for the $(\tilde{H},\tilde{W})$ models. The limits are projected on to a two-dimensional plane as a function of the wino/higgsino mass parameters: $(M_2,\mu)$. For the limits shown on the $(M_2,\mu)$ plane, the excluded regions are indicated by the area inside the contours. The expected limits for the 1$\sigma$ down variation are not shown as no mass points could be excluded. The round excluded area in the top part corresponds to the excluded parameter space in the $(\tilde{W},~\tilde{H})$ model $(M_{2} > |\mu|)$, while the two small areas in at the bottom are that in the $(\tilde{H},~\tilde{W})$ model $(M_{2} < |\mu|)$.

95% CL exclusion limits for the $(\tilde{H},\tilde{W})$ models. The limits are projected on to a two-dimensional plane as a function of the wino/higgsino mass parameters: $(M_2,\mu)$. For the limits shown on the $(M_2,\mu)$ plane, the excluded regions are indicated by the area inside the contours. The expected limits for the 1$\sigma$ down variation are not shown as no mass points could be excluded. The round excluded area in the top part corresponds to the excluded parameter space in the $(\tilde{W},~\tilde{H})$ model $(M_{2} > |\mu|)$, while the two small areas in at the bottom are that in the $(\tilde{H},~\tilde{W})$ model $(M_{2} < |\mu|)$.

Expected (dashed) and observed (solid red) 95% CL exclusion limit derived for the $(\tilde{H},\tilde{G})$ model, as a function of the lightest higgsino mass ($m(\tilde{\chi}_{1}^{0})$) and the branching ratio $\mathcal{B}(\tilde{\chi}_{1}^{0} \to Z\tilde{G}) (=1-\mathcal{B}(\tilde{\chi}_{1}^{0} \to h\tilde{G}))$. The excluded region is indicated by the area inside the contour.

Expected (dashed) and observed (solid red) 95% CL exclusion limit derived for the $(\tilde{H},\tilde{G})$ model, as a function of the lightest higgsino mass ($m(\tilde{\chi}_{1}^{0})$) and the branching ratio $\mathcal{B}(\tilde{\chi}_{1}^{0} \to Z\tilde{G}) (=1-\mathcal{B}(\tilde{\chi}_{1}^{0} \to h\tilde{G}))$. The excluded region is indicated by the area inside the contour.

Expected (dashed) and observed (solid red) 95% CL exclusion limit derived for the $(\tilde{H},\tilde{G})$ model, as a function of the lightest higgsino mass ($m(\tilde{\chi}_{1}^{0})$) and the branching ratio $\mathcal{B}(\tilde{\chi}_{1}^{0} \to Z\tilde{G}) (=1-\mathcal{B}(\tilde{\chi}_{1}^{0} \to h\tilde{G}))$. The excluded region is indicated by the area inside the contour.

Expected (dashed) and observed (solid red) 95% CL exclusion limit derived for the $(\tilde{H},\tilde{G})$ model, as a function of the lightest higgsino mass ($m(\tilde{\chi}_{1}^{0})$) and the branching ratio $\mathcal{B}(\tilde{\chi}_{1}^{0} \to Z\tilde{G}) (=1-\mathcal{B}(\tilde{\chi}_{1}^{0} \to h\tilde{G}))$. The excluded region is indicated by the area inside the contour.

Expected (dashed) and observed (solid red) 95% CL exclusion limit derived for the $(\tilde{H},\tilde{G})$ model, as a function of the lightest higgsino mass ($m(\tilde{\chi}_{1}^{0})$) and the branching ratio $\mathcal{B}(\tilde{\chi}_{1}^{0} \to Z\tilde{G}) (=1-\mathcal{B}(\tilde{\chi}_{1}^{0} \to h\tilde{G}))$. The excluded region is indicated by the area inside the contour.

Expected (dashed) and observed (solid red) 95% CL exclusion limit derived for the $(\tilde{H},\tilde{G})$ model, as a function of the lightest higgsino mass ($m(\tilde{\chi}_{1}^{0})$) and the branching ratio $\mathcal{B}(\tilde{\chi}_{1}^{0} \to Z\tilde{G}) (=1-\mathcal{B}(\tilde{\chi}_{1}^{0} \to h\tilde{G}))$. The excluded region is indicated by the area inside the contour.

95% CL exclusion limits for the $(\tilde{H},\tilde{a})$ model as the function of axino mass ($m(\tilde{a})$) and the lightest higgsino ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed lines) and observed (solid lines) limits with various $\mathcal{B}(\tilde{\chi}_{1}^{0} \to Z\tilde{a}) (=1-\mathcal{B}(\tilde{\chi}_{1}^{0} \to h\tilde{a}))$ hypotheses. No expected limit is derived for the case with $\mathcal{B}(\tilde{\chi}_{1}^{0} \to Z\tilde{a})=100$% as no mass point on the plane can be excluded.

95% CL exclusion limits for the $(\tilde{H},\tilde{a})$ model as the function of axino mass ($m(\tilde{a})$) and the lightest higgsino ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed line) and observed (solid red line) limits calculated for $\mathcal{B}(\tilde{\chi}_{1}^{0} \to Z\tilde{a})=100$%.

95% CL exclusion limits for the $(\tilde{H},\tilde{a})$ model as the function of axino mass ($m(\tilde{a})$) and the lightest higgsino ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed line) and observed (solid red line) limits calculated for $\mathcal{B}(\tilde{\chi}_{1}^{0} \to Z\tilde{a})=100$%.

95% CL exclusion limits for the $(\tilde{H},\tilde{a})$ model as the function of axino mass ($m(\tilde{a})$) and the lightest higgsino ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed lines) and observed (solid lines) limits with various $\mathcal{B}(\tilde{\chi}_{1}^{0} \to Z\tilde{a}) (=1-\mathcal{B}(\tilde{\chi}_{1}^{0} \to h\tilde{a}))$ hypotheses. No expected limit is derived for the case with $\mathcal{B}(\tilde{\chi}_{1}^{0} \to Z\tilde{a})=100$% as no mass point on the plane can be excluded.

95% CL exclusion limits for the $(\tilde{H},\tilde{a})$ model as the function of axino mass ($m(\tilde{a})$) and the lightest higgsino ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed line) and observed (solid red line) limits calculated for $\mathcal{B}(\tilde{\chi}_{1}^{0} \to Z\tilde{a})=100$%.

95% CL exclusion limits for the $(\tilde{H},\tilde{a})$ model as the function of axino mass ($m(\tilde{a})$) and the lightest higgsino ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed line) and observed (solid red line) limits calculated for $\mathcal{B}(\tilde{\chi}_{1}^{0} \to Z\tilde{a})=100$%.

95% CL exclusion limits for the $(\tilde{H},\tilde{a})$ model as the function of axino mass ($m(\tilde{a})$) and the lightest higgsino ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed lines) and observed (solid lines) limits with various $\mathcal{B}(\tilde{\chi}_{1}^{0} \to Z\tilde{a}) (=1-\mathcal{B}(\tilde{\chi}_{1}^{0} \to h\tilde{a}))$ hypotheses. No expected limit is derived for the case with $\mathcal{B}(\tilde{\chi}_{1}^{0} \to Z\tilde{a})=75$% as no mass point on the plane can be excluded.

95% CL exclusion limits for the $(\tilde{H},\tilde{a})$ model as the function of axino mass ($m(\tilde{a})$) and the lightest higgsino ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed lines) and observed (solid lines) limits with various $\mathcal{B}(\tilde{\chi}_{1}^{0} \to Z\tilde{a}) (=1-\mathcal{B}(\tilde{\chi}_{1}^{0} \to h\tilde{a}))$ hypotheses. No expected limit is derived for the case with $\mathcal{B}(\tilde{\chi}_{1}^{0} \to Z\tilde{a})=75$% as no mass point on the plane can be excluded.

95% CL exclusion limits for the $(\tilde{H},\tilde{a})$ model as the function of axino mass ($m(\tilde{a})$) and the lightest higgsino ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed lines) and observed (solid lines) limits with various $\mathcal{B}(\tilde{\chi}_{1}^{0} \to Z\tilde{a}) (=1-\mathcal{B}(\tilde{\chi}_{1}^{0} \to h\tilde{a}))$ hypotheses. No expected limit is derived for the case with $\mathcal{B}(\tilde{\chi}_{1}^{0} \to Z\tilde{a})=50$% as no mass point on the plane can be excluded.

95% CL exclusion limits for the $(\tilde{H},\tilde{a})$ model as the function of axino mass ($m(\tilde{a})$) and the lightest higgsino ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed lines) and observed (solid lines) limits with various $\mathcal{B}(\tilde{\chi}_{1}^{0} \to Z\tilde{a}) (=1-\mathcal{B}(\tilde{\chi}_{1}^{0} \to h\tilde{a}))$ hypotheses. No expected limit is derived for the case with $\mathcal{B}(\tilde{\chi}_{1}^{0} \to Z\tilde{a})=50$% as no mass point on the plane can be excluded.

95% CL exclusion limits for the $(\tilde{H},\tilde{a})$ model as the function of axino mass ($m(\tilde{a})$) and the lightest higgsino ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed lines) and observed (solid lines) limits with various $\mathcal{B}(\tilde{\chi}_{1}^{0} \to Z\tilde{a}) (=1-\mathcal{B}(\tilde{\chi}_{1}^{0} \to h\tilde{a}))$ hypotheses. No expected limit is derived for the case with $\mathcal{B}(\tilde{\chi}_{1}^{0} \to Z\tilde{a})=25$% as no mass point on the plane can be excluded.

The $\tilde{\chi}_{\textrm{heavy}}$ branching ratios in the $(\tilde{W},\tilde{H})$ model ($\tan\beta=10, \mu>0$). The branching ratios of wino-like chargino ($\tilde{\chi}_{2}^{\pm}$) and wino-like neutralino ($\tilde{\chi}_{3}^{0}$) are shown as the function of the mass of $\tilde{\chi}_{2}^{\pm}$ and that of the lightest higgsino-like neutralino ($\tilde{\chi}_{1}^{0}$), representing $m(\tilde{\chi}_{\textrm{light}})$ and $m(\tilde{\chi}_{\textrm{heavy}})$ respectively. The branchings into the two neutral higgsinos are summed up in the presentation i.e. $\mathcal{B}(\dots \rightarrow \tilde{\chi}_{1,2}^{0}) := \mathcal{B}(\dots \rightarrow \tilde{\chi}_{1}^{0})+\mathcal{B}(\dots \rightarrow \tilde{\chi}_{2}^{0})$.

The $\tilde{\chi}_{\textrm{heavy}}$ branching ratios in the $(\tilde{W},\tilde{H})$ model ($\tan\beta=10, \mu>0$). The branching ratios of wino-like chargino ($\tilde{\chi}_{2}^{\pm}$) and wino-like neutralino ($\tilde{\chi}_{3}^{0}$) are shown as the function of the mass of $\tilde{\chi}_{2}^{\pm}$ and that of the lightest higgsino-like neutralino ($\tilde{\chi}_{1}^{0}$), representing $m(\tilde{\chi}_{\textrm{light}})$ and $m(\tilde{\chi}_{\textrm{heavy}})$ respectively. The branchings into the two neutral higgsinos are summed up in the presentation i.e. $\mathcal{B}(\dots \rightarrow \tilde{\chi}_{1,2}^{0}) := \mathcal{B}(\dots \rightarrow \tilde{\chi}_{1}^{0})+\mathcal{B}(\dots \rightarrow \tilde{\chi}_{2}^{0})$.

The $\tilde{\chi}_{\textrm{heavy}}$ branching ratios in the $(\tilde{W},\tilde{H})$ model ($\tan\beta=10, \mu>0$). The branching ratios of wino-like chargino ($\tilde{\chi}_{2}^{\pm}$) and wino-like neutralino ($\tilde{\chi}_{3}^{0}$) are shown as the function of the mass of $\tilde{\chi}_{2}^{\pm}$ and that of the lightest higgsino-like neutralino ($\tilde{\chi}_{1}^{0}$), representing $m(\tilde{\chi}_{\textrm{light}})$ and $m(\tilde{\chi}_{\textrm{heavy}})$ respectively. The branchings into the two neutral higgsinos are summed up in the presentation i.e. $\mathcal{B}(\dots \rightarrow \tilde{\chi}_{1,2}^{0}) := \mathcal{B}(\dots \rightarrow \tilde{\chi}_{1}^{0})+\mathcal{B}(\dots \rightarrow \tilde{\chi}_{2}^{0})$.

The $\tilde{\chi}_{\textrm{heavy}}$ branching ratios in the $(\tilde{W},\tilde{H})$ model ($\tan\beta=10, \mu>0$). The branching ratios of wino-like chargino ($\tilde{\chi}_{2}^{\pm}$) and wino-like neutralino ($\tilde{\chi}_{3}^{0}$) are shown as the function of the mass of $\tilde{\chi}_{2}^{\pm}$ and that of the lightest higgsino-like neutralino ($\tilde{\chi}_{1}^{0}$), representing $m(\tilde{\chi}_{\textrm{light}})$ and $m(\tilde{\chi}_{\textrm{heavy}})$ respectively. The branchings into the two neutral higgsinos are summed up in the presentation i.e. $\mathcal{B}(\dots \rightarrow \tilde{\chi}_{1,2}^{0}) := \mathcal{B}(\dots \rightarrow \tilde{\chi}_{1}^{0})+\mathcal{B}(\dots \rightarrow \tilde{\chi}_{2}^{0})$.

The $\tilde{\chi}_{\textrm{heavy}}$ branching ratios in the $(\tilde{W},\tilde{H})$ model ($\tan\beta=10, \mu>0$). The branching ratios of wino-like chargino ($\tilde{\chi}_{2}^{\pm}$) and wino-like neutralino ($\tilde{\chi}_{3}^{0}$) are shown as the function of the mass of $\tilde{\chi}_{2}^{\pm}$ and that of the lightest higgsino-like neutralino ($\tilde{\chi}_{1}^{0}$), representing $m(\tilde{\chi}_{\textrm{light}})$ and $m(\tilde{\chi}_{\textrm{heavy}})$ respectively. The branchings into the two neutral higgsinos are summed up in the presentation i.e. $\mathcal{B}(\dots \rightarrow \tilde{\chi}_{1,2}^{0}) := \mathcal{B}(\dots \rightarrow \tilde{\chi}_{1}^{0})+\mathcal{B}(\dots \rightarrow \tilde{\chi}_{2}^{0})$.

The $\tilde{\chi}_{\textrm{heavy}}$ branching ratios in the $(\tilde{W},\tilde{H})$ model ($\tan\beta=10, \mu>0$). The branching ratios of wino-like chargino ($\tilde{\chi}_{2}^{\pm}$) and wino-like neutralino ($\tilde{\chi}_{3}^{0}$) are shown as the function of the mass of $\tilde{\chi}_{2}^{\pm}$ and that of the lightest higgsino-like neutralino ($\tilde{\chi}_{1}^{0}$), representing $m(\tilde{\chi}_{\textrm{light}})$ and $m(\tilde{\chi}_{\textrm{heavy}})$ respectively. The branchings into the two neutral higgsinos are summed up in the presentation i.e. $\mathcal{B}(\dots \rightarrow \tilde{\chi}_{1,2}^{0}) := \mathcal{B}(\dots \rightarrow \tilde{\chi}_{1}^{0})+\mathcal{B}(\dots \rightarrow \tilde{\chi}_{2}^{0})$.

The $\tilde{\chi}_{\textrm{heavy}}$ branching ratios in the $(\tilde{H},\tilde{W})$ model ($\tan\beta=10, \mu>0$). The branching ratios of higgsino-like chargino ($\tilde{\chi}_{2}^{\pm}$) and higgsino-like neutralinos ($\tilde{\chi}_{1}^{0}$, $\tilde{\chi}_{3}^{0}$) as the function of the mass of $\tilde{\chi}_{2}^{\pm}$ and that of wino-like neutralino ($\tilde{\chi}_{1}^{0}$), representing $m(\tilde{\chi}_{\textrm{light}})$ and $m(\tilde{\chi}_{\textrm{heavy}})$ respectively.

The $\tilde{\chi}_{\textrm{heavy}}$ branching ratios in the $(\tilde{H},\tilde{W})$ model ($\tan\beta=10, \mu>0$). The branching ratios of higgsino-like chargino ($\tilde{\chi}_{2}^{\pm}$) and higgsino-like neutralinos ($\tilde{\chi}_{1}^{0}$, $\tilde{\chi}_{3}^{0}$) as the function of the mass of $\tilde{\chi}_{2}^{\pm}$ and that of wino-like neutralino ($\tilde{\chi}_{1}^{0}$), representing $m(\tilde{\chi}_{\textrm{light}})$ and $m(\tilde{\chi}_{\textrm{heavy}})$ respectively.

The $\tilde{\chi}_{\textrm{heavy}}$ branching ratios in the $(\tilde{H},\tilde{W})$ model ($\tan\beta=10, \mu>0$). The branching ratios of higgsino-like chargino ($\tilde{\chi}_{2}^{\pm}$) and higgsino-like neutralinos ($\tilde{\chi}_{1}^{0}$, $\tilde{\chi}_{3}^{0}$) as the function of the mass of $\tilde{\chi}_{2}^{\pm}$ and that of wino-like neutralino ($\tilde{\chi}_{1}^{0}$), representing $m(\tilde{\chi}_{\textrm{light}})$ and $m(\tilde{\chi}_{\textrm{heavy}})$ respectively.

The $\tilde{\chi}_{\textrm{heavy}}$ branching ratios in the $(\tilde{H},\tilde{W})$ model ($\tan\beta=10, \mu>0$). The branching ratios of higgsino-like chargino ($\tilde{\chi}_{2}^{\pm}$) and higgsino-like neutralinos ($\tilde{\chi}_{1}^{0}$, $\tilde{\chi}_{3}^{0}$) as the function of the mass of $\tilde{\chi}_{2}^{\pm}$ and that of wino-like neutralino ($\tilde{\chi}_{1}^{0}$), representing $m(\tilde{\chi}_{\textrm{light}})$ and $m(\tilde{\chi}_{\textrm{heavy}})$ respectively.

The $\tilde{\chi}_{\textrm{heavy}}$ branching ratios in the $(\tilde{H},\tilde{W})$ model ($\tan\beta=10, \mu>0$). The branching ratios of higgsino-like chargino ($\tilde{\chi}_{2}^{\pm}$) and higgsino-like neutralinos ($\tilde{\chi}_{1}^{0}$, $\tilde{\chi}_{3}^{0}$) as the function of the mass of $\tilde{\chi}_{2}^{\pm}$ and that of wino-like neutralino ($\tilde{\chi}_{1}^{0}$), representing $m(\tilde{\chi}_{\textrm{light}})$ and $m(\tilde{\chi}_{\textrm{heavy}})$ respectively.

The $\tilde{\chi}_{\textrm{heavy}}$ branching ratios in the $(\tilde{H},\tilde{W})$ model ($\tan\beta=10, \mu>0$). The branching ratios of higgsino-like chargino ($\tilde{\chi}_{2}^{\pm}$) and higgsino-like neutralinos ($\tilde{\chi}_{1}^{0}$, $\tilde{\chi}_{3}^{0}$) as the function of the mass of $\tilde{\chi}_{2}^{\pm}$ and that of wino-like neutralino ($\tilde{\chi}_{1}^{0}$), representing $m(\tilde{\chi}_{\textrm{light}})$ and $m(\tilde{\chi}_{\textrm{heavy}})$ respectively.

The $\tilde{\chi}_{\textrm{heavy}}$ branching ratios in the $(\tilde{H},\tilde{W})$ model ($\tan\beta=10, \mu>0$). The branching ratios of higgsino-like chargino ($\tilde{\chi}_{2}^{\pm}$) and higgsino-like neutralinos ($\tilde{\chi}_{1}^{0}$, $\tilde{\chi}_{3}^{0}$) as the function of the mass of $\tilde{\chi}_{2}^{\pm}$ and that of wino-like neutralino ($\tilde{\chi}_{1}^{0}$), representing $m(\tilde{\chi}_{\textrm{light}})$ and $m(\tilde{\chi}_{\textrm{heavy}})$ respectively.

The $\tilde{\chi}_{\textrm{heavy}}$ branching ratios in the $(\tilde{H},\tilde{W})$ model ($\tan\beta=10, \mu>0$). The branching ratios of higgsino-like chargino ($\tilde{\chi}_{2}^{\pm}$) and higgsino-like neutralinos ($\tilde{\chi}_{1}^{0}$, $\tilde{\chi}_{3}^{0}$) as the function of the mass of $\tilde{\chi}_{2}^{\pm}$ and that of wino-like neutralino ($\tilde{\chi}_{1}^{0}$), representing $m(\tilde{\chi}_{\textrm{light}})$ and $m(\tilde{\chi}_{\textrm{heavy}})$ respectively.

The $\tilde{\chi}_{\textrm{heavy}}$ branching ratios in the $(\tilde{H},\tilde{W})$ model ($\tan\beta=10, \mu>0$). The branching ratios of higgsino-like chargino ($\tilde{\chi}_{2}^{\pm}$) and higgsino-like neutralinos ($\tilde{\chi}_{1}^{0}$, $\tilde{\chi}_{3}^{0}$) as the function of the mass of $\tilde{\chi}_{2}^{\pm}$ and that of wino-like neutralino ($\tilde{\chi}_{1}^{0}$), representing $m(\tilde{\chi}_{\textrm{light}})$ and $m(\tilde{\chi}_{\textrm{heavy}})$ respectively.

Expected (dashed) and observed (solid) 95% CL exclusion limits on $(\tilde{W},~\tilde{B})$-SIM model (C1C1-WW). The black numbers represents the expected cross-section upper-limits.

Expected (dashed) and observed (solid) 95% CL exclusion limits on $(\tilde{W},~\tilde{B})$-SIM model (C1N2-WZ). The black numbers represents the expected cross-section upper-limits.

Expected (dashed) and observed (solid) 95% CL exclusion limits on $(\tilde{W},~\tilde{B})$-SIM model (C1N2-Wh). The black numbers represents the expected cross-section upper-limits.

Expected (dashed) and observed (solid) 95% CL exclusion limits on $(\tilde{H},\tilde{G})$ models. The black numbers represents the expected cross-section upper-limits.

Expected (dashed) and observed (solid) 95% CL exclusion limits on $(\tilde{W},~\tilde{B})$-SIM model (C1C1-WW). The black numbers represents the observed cross-section upper-limits.

Expected (dashed) and observed (solid) 95% CL exclusion limits on $(\tilde{W},~\tilde{B})$-SIM model (C1N2-WZ). The black numbers represents the observed cross-section upper-limits.

Expected (dashed) and observed (solid) 95% CL exclusion limits on $(\tilde{W},~\tilde{B})$-SIM model (C1N2-Wh). The black numbers represents the observed cross-section upper-limits.

Expected (dashed) and observed (solid) 95% CL exclusion limits on $(\tilde{H},\tilde{G})$ models. The black numbers represents the observed cross-section upper-limits.

Signal acceptance of $(\tilde{W},\tilde{B})$ simplified models (C1C1-WW) by their most relevant SRs, evaluated using MC simulation. The acceptance is given by the ratio of weighted selected events by the SR to the weighted total generated events including all the $W/Z/h$ decays. The selection is based on generator-level particle information. The efficiency of lepton reconstruction/identification, $b$-tagging, as well as the $D_2$ and $n_{\textrm{trk}}$ selection in the $W_{qq}$/$Z_{qq}$-tagging are treated as 100%.

Signal acceptance of $(\tilde{W},\tilde{B})$ simplified models (C1N2-WZ) by their most relevant SRs, evaluated using MC simulation. The acceptance is given by the ratio of weighted selected events by the SR to the weighted total generated events including all the $W/Z/h$ decays. The selection is based on generator-level particle information. The efficiency of lepton reconstruction/identification, $b$-tagging, as well as the $D_2$ and $n_{\textrm{trk}}$ selection in the $W_{qq}$/$Z_{qq}$-tagging are treated as 100%.

Signal acceptance of $(\tilde{W},\tilde{B})$ simplified models (C1N2-WZ) by their most relevant SRs, evaluated using MC simulation. The acceptance is given by the ratio of weighted selected events by the SR to the weighted total generated events including all the $W/Z/h$ decays. The selection is based on generator-level particle information. The efficiency of lepton reconstruction/identification, $b$-tagging, as well as the $D_2$ and $n_{\textrm{trk}}$ selection in the $W_{qq}$/$Z_{qq}$-tagging are treated as 100%.

Signal acceptance of $(\tilde{W},\tilde{B})$ simplified models (C1N2-Wh) by their most relevant SRs, evaluated using MC simulation. The acceptance is given by the ratio of weighted selected events by the SR to the weighted total generated events including all the $W/Z/h$ decays. The selection is based on generator-level particle information. The efficiency of lepton reconstruction/identification, $b$-tagging, as well as the $D_2$ and $n_{\textrm{trk}}$ selection in the $W_{qq}$/$Z_{qq}$-tagging are treated as 100%.

Signal acceptance of $(\tilde{H},\tilde{B})$ simplified models (N2N3-ZZ) by their most relevant SRs, evaluated using MC simulation. The acceptance is given by the ratio of weighted selected events by the SR to the weighted total generated events including all the $W/Z/h$ decays. The selection is based on generator-level particle information. The efficiency of lepton reconstruction/identification, $b$-tagging, as well as the $D_2$ and $n_{\textrm{trk}}$ selection in the $W_{qq}$/$Z_{qq}$-tagging are treated as 100%. Acceptance below 0.005\% is rounded to 0.00 in the entry.

Signal acceptance of $(\tilde{H},\tilde{B})$ simplified models (N2N3-ZZ) by their most relevant SRs, evaluated using MC simulation. The acceptance is given by the ratio of weighted selected events by the SR to the weighted total generated events including all the $W/Z/h$ decays. The selection is based on generator-level particle information. The efficiency of lepton reconstruction/identification, $b$-tagging, as well as the $D_2$ and $n_{\textrm{trk}}$ selection in the $W_{qq}$/$Z_{qq}$-tagging are treated as 100%. Acceptance below 0.005\% is rounded to 0.00 in the entry.

Signal acceptance of $(\tilde{H},\tilde{B})$ simplified models (N2N3-Zh) by their most relevant SRs, evaluated using MC simulation. The acceptance is given by the ratio of weighted selected events by the SR to the weighted total generated events including all the $W/Z/h$ decays. The selection is based on generator-level particle information. The efficiency of lepton reconstruction/identification, $b$-tagging, as well as the $D_2$ and $n_{\textrm{trk}}$ selection in the $W_{qq}$/$Z_{qq}$-tagging are treated as 100%. Acceptance below 0.005\% is rounded to 0.00 in the entry.

Signal acceptance of $(\tilde{H},\tilde{B})$ simplified models (N2N3-hh) by their most relevant SRs, evaluated using MC simulation. The acceptance is given by the ratio of weighted selected events by the SR to the weighted total generated events including all the $W/Z/h$ decays. The selection is based on generator-level particle information. The efficiency of lepton reconstruction/identification, $b$-tagging, as well as the $D_2$ and $n_{\textrm{trk}}$ selection in the $W_{qq}$/$Z_{qq}$-tagging are treated as 100%. Acceptance below 0.005\% is rounded to 0.00 in the entry.

Signal acceptance of the $(\tilde{H},\tilde{G})$ model by SR-4Q-VV, evaluated using MC simulation. The acceptance is given by the ratio of weighted selected events by the SR to the weighted total generated events including all the $W/Z/h$ decays. The selection is based on generator-level particle information. The efficiency of lepton reconstruction/identification, $b$-tagging, as well as the $D_2$ and $n_{\textrm{trk}}$ selection in the $W_{qq}$/$Z_{qq}$-tagging are treated as 100%. Acceptance below 0.005\% is rounded to 0.00 in the entry.

Signal acceptance of the $(\tilde{H},\tilde{G})$ model by SR-2B2Q-VZ, evaluated using MC simulation. The acceptance is given by the ratio of weighted selected events by the SR to the weighted total generated events including all the $W/Z/h$ decays. The selection is based on generator-level particle information. The efficiency of lepton reconstruction/identification, $b$-tagging, as well as the $D_2$ and $n_{\textrm{trk}}$ selection in the $W_{qq}$/$Z_{qq}$-tagging are treated as 100%. Acceptance below 0.005\% is rounded to 0.00 in the entry.

Signal acceptance of the $(\tilde{H},\tilde{G})$ model by SR-2B2Q-Vh, evaluated using MC simulation. The acceptance is given by the ratio of weighted selected events by the SR to the weighted total generated events including all the $W/Z/h$ decays. The selection is based on generator-level particle information. The efficiency of lepton reconstruction/identification, $b$-tagging, as well as the $D_2$ and $n_{\textrm{trk}}$ selection in the $W_{qq}$/$Z_{qq}$-tagging are treated as 100%. Acceptance below 0.005\% is rounded to 0.00 in the entry.

Efficiency for $(\tilde{W},\tilde{B})$ simplified models (C1C1-WW) in their most relevant SRs. The efficiency in a given SR is defined by the ratio of weighted events selected based on the generator-level particle information and that based on detector simulation and particle reconstruction. This mainly accounts for the efficiency of lepton reconstruction/identification, $b$-tagging, as well as the $D_2$ and $n_{\textrm{trk}}$ selection in the and $W_{qq}$/$Z_{qq}$-tagging.

Efficiency for $(\tilde{W},\tilde{B})$ simplified models (C1N2-WZ) in their most relevant SRs. The efficiency in a given SR is defined by the ratio of weighted events selected based on the generator-level particle information and that based on detector simulation and particle reconstruction. This mainly accounts for the efficiency of lepton reconstruction/identification, $b$-tagging, as well as the $D_2$ and $n_{\textrm{trk}}$ selection in the and $W_{qq}$/$Z_{qq}$-tagging.

Efficiency for $(\tilde{W},\tilde{B})$ simplified models (C1N2-WZ) in their most relevant SRs. The efficiency in a given SR is defined by the ratio of weighted events selected based on the generator-level particle information and that based on detector simulation and particle reconstruction. This mainly accounts for the efficiency of lepton reconstruction/identification, $b$-tagging, as well as the $D_2$ and $n_{\textrm{trk}}$ selection in the and $W_{qq}$/$Z_{qq}$-tagging.

Efficiency for $(\tilde{W},\tilde{B})$ simplified models (C1N2-Wh) in their most relevant SRs. The efficiency in a given SR is defined by the ratio of weighted events selected based on the generator-level particle information and that based on detector simulation and particle reconstruction. This mainly accounts for the efficiency of lepton reconstruction/identification, $b$-tagging, as well as the $D_2$ and $n_{\textrm{trk}}$ selection in the and $W_{qq}$/$Z_{qq}$-tagging.

Efficiency for $(\tilde{H},\tilde{B})$ simplified models (N2N3-ZZ) in their most relevant SRs. The efficiency in a given SR is defined by the ratio of weighted events selected based on the generator-level particle information and that based on detector simulation and particle reconstruction. This mainly accounts for the efficiency of lepton reconstruction/identification, $b$-tagging, as well as the $D_2$ and $n_{\textrm{trk}}$ selection in the and $W_{qq}$/$Z_{qq}$-tagging. Efficiency below 0.005\% is rounded to 0.00 in the entry.

Efficiency for $(\tilde{H},\tilde{B})$ simplified models (N2N3-ZZ) in their most relevant SRs. The efficiency in a given SR is defined by the ratio of weighted events selected based on the generator-level particle information and that based on detector simulation and particle reconstruction. This mainly accounts for the efficiency of lepton reconstruction/identification, $b$-tagging, as well as the $D_2$ and $n_{\textrm{trk}}$ selection in the and $W_{qq}$/$Z_{qq}$-tagging. Efficiency below 0.005\% is rounded to 0.00 in the entry.

Efficiency for $(\tilde{H},\tilde{B})$ simplified models (N2N3-Zh) in their most relevant SRs. The efficiency in a given SR is defined by the ratio of weighted events selected based on the generator-level particle information and that based on detector simulation and particle reconstruction. This mainly accounts for the efficiency of lepton reconstruction/identification, $b$-tagging, as well as the $D_2$ and $n_{\textrm{trk}}$ selection in the and $W_{qq}$/$Z_{qq}$-tagging. Efficiency below 0.005\% is rounded to 0.00 in the entry.

Efficiency for $(\tilde{H},\tilde{B})$ simplified models (N2N3-hh) in their most relevant SRs. The efficiency in a given SR is defined by the ratio of weighted events selected based on the generator-level particle information and that based on detector simulation and particle reconstruction. This mainly accounts for the efficiency of lepton reconstruction/identification, $b$-tagging, as well as the $D_2$ and $n_{\textrm{trk}}$ selection in the and $W_{qq}$/$Z_{qq}$-tagging. Efficiency below 0.005\% is rounded to 0.00 in the entry.

Efficiency for $(\tilde{H},\tilde{G})$ in SR-4Q-VV. The efficiency in a given SR is defined by the ratio of weighted events selected based on the generator-level particle information and that based on detector simulation and particle reconstruction. This mainly accounts for the efficiency of lepton reconstruction/identification, $b$-tagging, as well as the $D_2$ and $n_{\textrm{trk}}$ selection in the and $W_{qq}$/$Z_{qq}$-tagging. Efficiency below 0.005\% is rounded to 0.00 in the entry. The spiky efficiency values (e.g. $m(\tilde{\chi}_{1}^{0})=600~\textrm{GeV}$ in SR-4Q-VV) are because of the difference between the truth and reconstructed samples amplified by a statistical fluctuation due to the limited statistics.

Efficiency for $(\tilde{H},\tilde{G})$ in SR-2B2Q-VZ. The efficiency in a given SR is defined by the ratio of weighted events selected based on the generator-level particle information and that based on detector simulation and particle reconstruction. This mainly accounts for the efficiency of lepton reconstruction/identification, $b$-tagging, as well as the $D_2$ and $n_{\textrm{trk}}$ selection in the and $W_{qq}$/$Z_{qq}$-tagging. Efficiency below 0.005\% is rounded to 0.00 in the entry. The spiky efficiency values (e.g. $m(\tilde{\chi}_{1}^{0})=600~\textrm{GeV}$ in SR-4Q-VV) are because of the difference between the truth and reconstructed samples amplified by a statistical fluctuation due to the limited statistics.

Efficiency for $(\tilde{H},\tilde{G})$ in SR-2B2Q-Vh. The efficiency in a given SR is defined by the ratio of weighted events selected based on the generator-level particle information and that based on detector simulation and particle reconstruction. This mainly accounts for the efficiency of lepton reconstruction/identification, $b$-tagging, as well as the $D_2$ and $n_{\textrm{trk}}$ selection in the and $W_{qq}$/$Z_{qq}$-tagging. Efficiency below 0.005\% is rounded to 0.00 in the entry. The spiky efficiency values (e.g. $m(\tilde{\chi}_{1}^{0})=600~\textrm{GeV}$ in SR-4Q-VV) are because of the difference between the truth and reconstructed samples amplified by a statistical fluctuation due to the limited statistics.

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Results for the spin-exotic $1^{-+}1^+[\pi\pi]_{1^{-\,-}}\pi P$ wave from the free-isobar partial-wave analysis performed in the fourth $t^\prime$ bin from $0.326$ to $1.000\;(\text{GeV}/c)^2$. The plotted values represent the intensity of the coherent sum of the dynamic isobar amplitudes $\{\mathcal{T}_k^\text{fit}\}$ as a function of $m_{3\pi}$, where the coherent sums run over all $m_{\pi^-\pi^+}$ bins indexed by $k$. These intensity values are given in number of events per $40\;\text{MeV}/c^2$ $m_{3\pi}$ interval and correspond to the orange points in Fig. 8(b). In the "Resources" section of this $t^\prime$ bin, we provide the JSON file named <code>transition_amplitudes_tBin_3.json</code> for download, which contains for each $m_{3\pi}$ bin the values of the transition amplitudes $\{\mathcal{T}_k^\text{fit}\}$ for all $m_{\pi^-\pi^+}$ bins, their covariances, and further information. The data in this JSON file are organized in independent bins of $m_{3\pi}$. The information in these bins can be accessed via the key <code>m3pi_bin_<#>_t_prime_bin_3</code>. Each independent $m_{3\pi}$ bin contains <ul> <li>the kinematic ranges of the $(m_{3\pi}, t^\prime)$ cell, which are accessible via the keys <code>m3pi_lower_limit</code>, <code>m3pi_upper_limit</code>, <code>t_prime_lower_limit</code>, and <code>t_prime_upper_limit</code>.</li> <li>the $m_{\pi^-\pi^+}$ bin borders, which are accessible via the keys <code>m2pi_lower_limits</code> and <code>m2pi_upper_limits</code>.</li> <li>the real and imaginary parts of the transition amplitudes $\{\mathcal{T}_k^\text{fit}\}$ for all $m_{\pi^-\pi^+}$ bins, which are accessible via the keys <code>transition_amplitudes_real_part</code> and <code>transition_amplitudes_imag_part</code>, respectively.</li> <li>the covariance matrix of the real and imaginary parts of the $\{\mathcal{T}_k^\text{fit}\}$ for all $m_{\pi^-\pi^+}$ bins, which is accessible via the key <code>covariance_matrix</code>. Note that this matrix is real-valued and that its rows and columns are indexed such that $(\Re,\Im)$ pairs of the transition amplitudes are arranged with increasing $k$.</li> <li>the normalization factors $\mathcal{N}_a$ in Eq. (13) for all $m_{\pi^-\pi^+}$ bins, which are accessible via the key <code>normalization_factors</code>.</li> <li>the shape of the zero mode, i.e., the values of $\tilde\Delta_k$ for all $m_{\pi^-\pi^+}$ bins, which is accessible via the key <code>zero_mode_shape</code>.</li> <li>the reference wave, which is accessible via the key <code>reference_wave</code>. Note that this is always the $4^{++}1^+\rho(770)\pi G$ wave.</li> </ul>

$K^-$ (a), invariant yields as a function of $m_T-m_0$ for various rapidity regions in 10--40\% central Au+Au collisions at ${\sqrt{s_{\mathrm{NN}}} = \mathrm{3\,GeV}}$. Statistics and systematic uncertainties are added quadratic here for plotting. Solid and dashed black lines depict $m_T$ exponential function fits to the measured data points with arbitrate scaling factors in each rapidity windows.

$\phi$ meson (b) invariant yields as a function of $m_T-m_0$ for various rapidity regions in 10--40\% central Au+Au collisions at ${\sqrt{s_{\mathrm{NN}}} = \mathrm{3\,GeV}}$. Statistics and systematic uncertainties are added quadratic here for plotting. Solid and dashed black lines depict $m_T$ exponential function fits to the measured data points with arbitrate scaling factors in each rapidity windows.

$\Xi^-$ (c) invariant yields as a function of $m_T-m_0$ for various rapidity regions in 10--40\% central Au+Au collisions at ${\sqrt{s_{\mathrm{NN}}} = \mathrm{3\,GeV}}$. Statistics and systematic uncertainties are added quadratic here for plotting. Solid and dashed black lines depict $m_T$ exponential function fits to the measured data points with arbitrate scaling factors in each rapidity windows.

$K^-$ (a), invariant yields as a function of $m_T-m_0$ for various rapidity regions in 40--60\% central Au+Au collisions at ${\sqrt{s_{\mathrm{NN}}} = \mathrm{3\,GeV}}$. Statistics and systematic uncertainties are added quadratic here for plotting. Solid and dashed black lines depict $m_T$ exponential function fits to the measured data points with arbitrate scaling factors in each rapidity windows.

$\phi$ meson (b) invariant yields as a function of $m_T-m_0$ for various rapidity regions in 40--60\% central Au+Au collisions at ${\sqrt{s_{\mathrm{NN}}} = \mathrm{3\,GeV}}$. Statistics and systematic uncertainties are added quadratic here for plotting. Solid and dashed black lines depict $m_T$ exponential function fits to the measured data points with arbitrate scaling factors in each rapidity windows.

Rapidity density distributions of $K^-$ (squares), $p_T$-integrated yields $dN/dy$ in 0--10\% (a), 10--40\% (b) and 40--60\% central (c) Au+Au collisions at ${\sqrt{s_{\mathrm{NN}}} = \mathrm{3\,GeV}}$. %The full symbols show the measured data, while the open ones are data reflected with respect to $y=0$ in the center-of-mass frame. Solid lines depict Gaussian function fits to the data points.

Rapidity density distributions of $\phi$ meson (circles) $p_T$-integrated yields $dN/dy$ in 0--10\% (a), 10--40\% (b) and 40--60\% central (c) Au+Au collisions at ${\sqrt{s_{\mathrm{NN}}} = \mathrm{3\,GeV}}$. %The full symbols show the measured data, while the open ones are data reflected with respect to $y=0$ in the center-of-mass frame. Solid lines depict Gaussian function fits to the data points.

Rapidity density distributions of $\Xi^-$ (diamonds) $p_T$-integrated yields $dN/dy$ in 0--10\% (a), 10--40\% (b) and 40--60\% central (c) Au+Au collisions at ${\sqrt{s_{\mathrm{NN}}} = \mathrm{3\,GeV}}$. %The full symbols show the measured data, while the open ones are data reflected with respect to $y=0$ in the center-of-mass frame. Solid lines depict Gaussian function fits to the data points.

$\phi/K^-$ (a) and $\phi/\Xi^-$ (b) ratio as a function of collision energy, $\sqrt{s_{\mathrm{NN}}}$. The solid black circles show the measurements presented here in 0-10\% centrality bin, while empty markers in black or grey are used for data from various other energies and/or collision systems. The grey solid line represents a THERMUS calculation based on the Grand Canonical Ensemble (GCE) while the dotted lines depict calculations based on the Canonical Ensemble (CE) with different parameters of strangeness correlation radius ($r_c$). The green dashed line, green shaded band and the solid red line show transport model calculations from the public versions $\mathrm{UrQMD}^{1}$, modified $\mathrm{UrQMD}^{2}$ and SMASH, respectively.

Rapidity($y$) dependence of $v_1$ (top panels) and $v_2$ (bottom panels) of proton and $\Lambda$ baryons (left panels), pions (middle panels) and kaons (right panels) in 10-40% centrality for the $\sqrt{s_{NN}}$ = 3GeV Au+Au collisions. Statistical and systematic uncertainties are shown as bars and gray bands, respectively. Some uncertainties are smaller than the data points. The UrQMD and JAM results are shown as bands:golden, red and blue bands stand for JAM mean-field, UrQMD mean-field and UrQMD cascade mode, respectively. The value of the incompressibility $\kappa$ = 380 MeV is used in the mean-field option. More detailed model descriptions and data comparisons can be found in Supplemental Material.

Rapidity($y$) dependence of $v_1$ (top panels) and $v_2$ (bottom panels) of proton and $\Lambda$ baryons (left panels), pions (middle panels) and kaons (right panels) in 10-40% centrality for the $\sqrt{s_{NN}}$ = 3GeV Au+Au collisions. Statistical and systematic uncertainties are shown as bars and gray bands, respectively. Some uncertainties are smaller than the data points. The UrQMD and JAM results are shown as bands:golden, red and blue bands stand for JAM mean-field, UrQMD mean-field and UrQMD cascade mode, respectively. The value of the incompressibility $\kappa$ = 380 MeV is used in the mean-field option. More detailed model descriptions and data comparisons can be found in Supplemental Material.

Rapidity($y$) dependence of $v_1$ (top panels) and $v_2$ (bottom panels) of proton and $\Lambda$ baryons (left panels), pions (middle panels) and kaons (right panels) in 10-40% centrality for the $\sqrt{s_{NN}}$ = 3GeV Au+Au collisions. Statistical and systematic uncertainties are shown as bars and gray bands, respectively. Some uncertainties are smaller than the data points. The UrQMD and JAM results are shown as bands:golden, red and blue bands stand for JAM mean-field, UrQMD mean-field and UrQMD cascade mode, respectively. The value of the incompressibility $\kappa$ = 380 MeV is used in the mean-field option. More detailed model descriptions and data comparisons can be found in Supplemental Material.

$v_2$ scaled by the number of constituent quarks, $v_2/n_q$ , as a function of scaled transverse kinetic energy ($(m_T − m_0)/n_q$) for pions, kaons and protons from Au+Au collisions in 10-40% centrality at $\sqrt{s_{NN}}$ = 3, 27, and 54.4 GeV for positive charged particles (left panel) and negative charged particles (right panel). Colored dashed lines represent the scaling fit to data in 7.7, 14.5, 27, 54.4, and 200 GeV Au+Au collisions from STAR experiment at RHIC [43–45]. Statistical and systematic uncertainties are shown as bars and gray bands, respectively. Some uncertainties are smaller than the data points.

$v_2$ scaled by the number of constituent quarks, $v_2/n_q$ , as a function of scaled transverse kinetic energy ($(m_T − m_0)/n_q$) for pions, kaons and protons from Au+Au collisions in 10-40% centrality at $\sqrt{s_{NN}}$ = 3, 27, and 54.4 GeV for positive charged particles (left panel) and negative charged particles (right panel). Colored dashed lines represent the scaling fit to data in 7.7, 14.5, 27, 54.4, and 200 GeV Au+Au collisions from STAR experiment at RHIC [43–45]. Statistical and systematic uncertainties are shown as bars and gray bands, respectively. Some uncertainties are smaller than the data points.

$v_2$ scaled by the number of constituent quarks, $v_2/n_q$ , as a function of scaled transverse kinetic energy ($(m_T − m_0)/n_q$) for pions, kaons and protons from Au+Au collisions in 10-40% centrality at $\sqrt{s_{NN}}$ = 3, 27, and 54.4 GeV for positive charged particles (left panel) and negative charged particles (right panel). Colored dashed lines represent the scaling fit to data in 7.7, 14.5, 27, 54.4, and 200 GeV Au+Au collisions from STAR experiment at RHIC [43–45]. Statistical and systematic uncertainties are shown as bars and gray bands, respectively. Some uncertainties are smaller than the data points.

$v_2$ scaled by the number of constituent quarks, $v_2/n_q$ , as a function of scaled transverse kinetic energy ($(m_T − m_0)/n_q$) for pions, kaons and protons from Au+Au collisions in 10-40% centrality at $\sqrt{s_{NN}}$ = 3, 27, and 54.4 GeV for positive charged particles (left panel) and negative charged particles (right panel). Colored dashed lines represent the scaling fit to data in 7.7, 14.5, 27, 54.4, and 200 GeV Au+Au collisions from STAR experiment at RHIC [43–45]. Statistical and systematic uncertainties are shown as bars and gray bands, respectively. Some uncertainties are smaller than the data points.

$v_2$ scaled by the number of constituent quarks, $v_2/n_q$ , as a function of scaled transverse kinetic energy ($(m_T − m_0)/n_q$) for pions, kaons and protons from Au+Au collisions in 10-40% centrality at $\sqrt{s_{NN}}$ = 3, 27, and 54.4 GeV for positive charged particles (left panel) and negative charged particles (right panel). Colored dashed lines represent the scaling fit to data in 7.7, 14.5, 27, 54.4, and 200 GeV Au+Au collisions from STAR experiment at RHIC [43–45]. Statistical and systematic uncertainties are shown as bars and gray bands, respectively. Some uncertainties are smaller than the data points.

$v_2$ scaled by the number of constituent quarks, $v_2/n_q$ , as a function of scaled transverse kinetic energy ($(m_T − m_0)/n_q$) for pions, kaons and protons from Au+Au collisions in 10-40% centrality at $\sqrt{s_{NN}}$ = 3, 27, and 54.4 GeV for positive charged particles (left panel) and negative charged particles (right panel). Colored dashed lines represent the scaling fit to data in 7.7, 14.5, 27, 54.4, and 200 GeV Au+Au collisions from STAR experiment at RHIC [43–45]. Statistical and systematic uncertainties are shown as bars and gray bands, respectively. Some uncertainties are smaller than the data points.

$v_2$ scaled by the number of constituent quarks, $v_2/n_q$ , as a function of scaled transverse kinetic energy ($(m_T − m_0)/n_q$) for pions, kaons and protons from Au+Au collisions in 10-40% centrality at $\sqrt{s_{NN}}$ = 3, 27, and 54.4 GeV for positive charged particles (left panel) and negative charged particles (right panel). Colored dashed lines represent the scaling fit to data in 7.7, 14.5, 27, 54.4, and 200 GeV Au+Au collisions from STAR experiment at RHIC [43–45]. Statistical and systematic uncertainties are shown as bars and gray bands, respectively. Some uncertainties are smaller than the data points.

$v_2$ scaled by the number of constituent quarks, $v_2/n_q$ , as a function of scaled transverse kinetic energy ($(m_T − m_0)/n_q$) for pions, kaons and protons from Au+Au collisions in 10-40% centrality at $\sqrt{s_{NN}}$ = 3, 27, and 54.4 GeV for positive charged particles (left panel) and negative charged particles (right panel). Colored dashed lines represent the scaling fit to data in 7.7, 14.5, 27, 54.4, and 200 GeV Au+Au collisions from STAR experiment at RHIC [43–45]. Statistical and systematic uncertainties are shown as bars and gray bands, respectively. Some uncertainties are smaller than the data points.

$v_2$ scaled by the number of constituent quarks, $v_2/n_q$ , as a function of scaled transverse kinetic energy ($(m_T − m_0)/n_q$) for pions, kaons and protons from Au+Au collisions in 10-40% centrality at $\sqrt{s_{NN}}$ = 3, 27, and 54.4 GeV for positive charged particles (left panel) and negative charged particles (right panel). Colored dashed lines represent the scaling fit to data in 7.7, 14.5, 27, 54.4, and 200 GeV Au+Au collisions from STAR experiment at RHIC [43–45]. Statistical and systematic uncertainties are shown as bars and gray bands, respectively. Some uncertainties are smaller than the data points.

$v_2$ scaled by the number of constituent quarks, $v_2/n_q$ , as a function of scaled transverse kinetic energy ($(m_T − m_0)/n_q$) for pions, kaons and protons from Au+Au collisions in 10-40% centrality at $\sqrt{s_{NN}}$ = 3, 27, and 54.4 GeV for positive charged particles (left panel) and negative charged particles (right panel). Colored dashed lines represent the scaling fit to data in 7.7, 14.5, 27, 54.4, and 200 GeV Au+Au collisions from STAR experiment at RHIC [43–45]. Statistical and systematic uncertainties are shown as bars and gray bands, respectively. Some uncertainties are smaller than the data points.

$v_2$ scaled by the number of constituent quarks, $v_2/n_q$ , as a function of scaled transverse kinetic energy ($(m_T − m_0)/n_q$) for pions, kaons and protons from Au+Au collisions in 10-40% centrality at $\sqrt{s_{NN}}$ = 3, 27, and 54.4 GeV for positive charged particles (left panel) and negative charged particles (right panel). Colored dashed lines represent the scaling fit to data in 7.7, 14.5, 27, 54.4, and 200 GeV Au+Au collisions from STAR experiment at RHIC [43–45]. Statistical and systematic uncertainties are shown as bars and gray bands, respectively. Some uncertainties are smaller than the data points.

$v_2$ scaled by the number of constituent quarks, $v_2/n_q$ , as a function of scaled transverse kinetic energy ($(m_T − m_0)/n_q$) for pions, kaons and protons from Au+Au collisions in 10-40% centrality at $\sqrt{s_{NN}}$ = 3, 27, and 54.4 GeV for positive charged particles (left panel) and negative charged particles (right panel). Colored dashed lines represent the scaling fit to data in 7.7, 14.5, 27, 54.4, and 200 GeV Au+Au collisions from STAR experiment at RHIC [43–45]. Statistical and systematic uncertainties are shown as bars and gray bands, respectively. Some uncertainties are smaller than the data points.

$v_2$ scaled by the number of constituent quarks, $v_2/n_q$ , as a function of scaled transverse kinetic energy ($(m_T − m_0)/n_q$) for pions, kaons and protons from Au+Au collisions in 10-40% centrality at $\sqrt{s_{NN}}$ = 3, 27, and 54.4 GeV for positive charged particles (left panel) and negative charged particles (right panel). Colored dashed lines represent the scaling fit to data in 7.7, 14.5, 27, 54.4, and 200 GeV Au+Au collisions from STAR experiment at RHIC [43–45]. Statistical and systematic uncertainties are shown as bars and gray bands, respectively. Some uncertainties are smaller than the data points.

$v_2$ scaled by the number of constituent quarks, $v_2/n_q$ , as a function of scaled transverse kinetic energy ($(m_T − m_0)/n_q$) for pions, kaons and protons from Au+Au collisions in 10-40% centrality at $\sqrt{s_{NN}}$ = 3, 27, and 54.4 GeV for positive charged particles (left panel) and negative charged particles (right panel). Colored dashed lines represent the scaling fit to data in 7.7, 14.5, 27, 54.4, and 200 GeV Au+Au collisions from STAR experiment at RHIC [43–45]. Statistical and systematic uncertainties are shown as bars and gray bands, respectively. Some uncertainties are smaller than the data points.

$v_2$ scaled by the number of constituent quarks, $v_2/n_q$ , as a function of scaled transverse kinetic energy ($(m_T − m_0)/n_q$) for pions, kaons and protons from Au+Au collisions in 10-40% centrality at $\sqrt{s_{NN}}$ = 3, 27, and 54.4 GeV for positive charged particles (left panel) and negative charged particles (right panel). Colored dashed lines represent the scaling fit to data in 7.7, 14.5, 27, 54.4, and 200 GeV Au+Au collisions from STAR experiment at RHIC [43–45]. Statistical and systematic uncertainties are shown as bars and gray bands, respectively. Some uncertainties are smaller than the data points.

$v_2$ scaled by the number of constituent quarks, $v_2/n_q$ , as a function of scaled transverse kinetic energy ($(m_T − m_0)/n_q$) for pions, kaons and protons from Au+Au collisions in 10-40% centrality at $\sqrt{s_{NN}}$ = 3, 27, and 54.4 GeV for positive charged particles (left panel) and negative charged particles (right panel). Colored dashed lines represent the scaling fit to data in 7.7, 14.5, 27, 54.4, and 200 GeV Au+Au collisions from STAR experiment at RHIC [43–45]. Statistical and systematic uncertainties are shown as bars and gray bands, respectively. Some uncertainties are smaller than the data points.

$v_2$ scaled by the number of constituent quarks, $v_2/n_q$ , as a function of scaled transverse kinetic energy ($(m_T − m_0)/n_q$) for pions, kaons and protons from Au+Au collisions in 10-40% centrality at $\sqrt{s_{NN}}$ = 3, 27, and 54.4 GeV for positive charged particles (left panel) and negative charged particles (right panel). Colored dashed lines represent the scaling fit to data in 7.7, 14.5, 27, 54.4, and 200 GeV Au+Au collisions from STAR experiment at RHIC [43–45]. Statistical and systematic uncertainties are shown as bars and gray bands, respectively. Some uncertainties are smaller than the data points.

Collision energy dependence of (top panel) directed flow slope $dv_1/dy|_{y=0}$ for p, $\Lambda, \pi$(combined from $\pi^{\pm}$), K(combined from $K^{\pm}$ and $K_S^0$), $\phi$ and $\Xi^−$, and (bottom panel) elliptic flow $v_2$ for p, $\pi$(combined from $\pi^{\pm}$) in heavy- ion collisions. Collision centrality for all data from RHIC is 10-40%, except for 4.5 GeV where 10-30% is for $dv_1/dy|_{y=0}$ and 0-30% is for $v_2$. Statistical and systematic uncertainties are shown as bars and gray bands, respectively. Some uncertainties are smaller than the data points. The JAM and UrQMD results are shown as colored bands:golden, red and blue bands stand for JAM mean-field, UrQMD mean-field and UrQMD cascade mode, respectively. For clarity the x-axis value of the data points have been shifted.

Collision energy dependence of (top panel) directed flow slope $dv_1/dy|_{y=0}$ for p, $\Lambda, \pi$(combined from $\pi^{\pm}$), K(combined from $K^{\pm}$ and $K_S^0$), $\phi$ and $\Xi^−$, and (bottom panel) elliptic flow $v_2$ for p, $\pi$(combined from $\pi^{\pm}$) in heavy- ion collisions. Collision centrality for all data from RHIC is 10-40%, except for 4.5 GeV where 10-30% is for $dv_1/dy|_{y=0}$ and 0-30% is for $v_2$. Statistical and systematic uncertainties are shown as bars and gray bands, respectively. Some uncertainties are smaller than the data points. The JAM and UrQMD results are shown as colored bands:golden, red and blue bands stand for JAM mean-field, UrQMD mean-field and UrQMD cascade mode, respectively. For clarity the x-axis value of the data points have been shifted.

Collision energy dependence of (top panel) directed flow slope $dv_1/dy|_{y=0}$ for p, $\Lambda, \pi$(combined from $\pi^{\pm}$), K(combined from $K^{\pm}$ and $K_S^0$), $\phi$ and $\Xi^−$, and (bottom panel) elliptic flow $v_2$ for p, $\pi$(combined from $\pi^{\pm}$) in heavy- ion collisions. Collision centrality for all data from RHIC is 10-40%, except for 4.5 GeV where 10-30% is for $dv_1/dy|_{y=0}$ and 0-30% is for $v_2$. Statistical and systematic uncertainties are shown as bars and gray bands, respectively. Some uncertainties are smaller than the data points. The JAM and UrQMD results are shown as colored bands:golden, red and blue bands stand for JAM mean-field, UrQMD mean-field and UrQMD cascade mode, respectively. For clarity the x-axis value of the data points have been shifted.

Collision energy dependence of (top panel) directed flow slope $dv_1/dy|_{y=0}$ for p, $\Lambda, \pi$(combined from $\pi^{\pm}$), K(combined from $K^{\pm}$ and $K_S^0$), $\phi$ and $\Xi^−$, and (bottom panel) elliptic flow $v_2$ for p, $\pi$(combined from $\pi^{\pm}$) in heavy- ion collisions. Collision centrality for all data from RHIC is 10-40%, except for 4.5 GeV where 10-30% is for $dv_1/dy|_{y=0}$ and 0-30% is for $v_2$. Statistical and systematic uncertainties are shown as bars and gray bands, respectively. Some uncertainties are smaller than the data points. The JAM and UrQMD results are shown as colored bands:golden, red and blue bands stand for JAM mean-field, UrQMD mean-field and UrQMD cascade mode, respectively. For clarity the x-axis value of the data points have been shifted.

Collision energy dependence of (top panel) directed flow slope $dv_1/dy|_{y=0}$ for p, $\Lambda, \pi$(combined from $\pi^{\pm}$), K(combined from $K^{\pm}$ and $K_S^0$), $\phi$ and $\Xi^−$, and (bottom panel) elliptic flow $v_2$ for p, $\pi$(combined from $\pi^{\pm}$) in heavy- ion collisions. Collision centrality for all data from RHIC is 10-40%, except for 4.5 GeV where 10-30% is for $dv_1/dy|_{y=0}$ and 0-30% is for $v_2$. Statistical and systematic uncertainties are shown as bars and gray bands, respectively. Some uncertainties are smaller than the data points. The JAM and UrQMD results are shown as colored bands:golden, red and blue bands stand for JAM mean-field, UrQMD mean-field and UrQMD cascade mode, respectively. For clarity the x-axis value of the data points have been shifted.

Collision energy dependence of (top panel) directed flow slope $dv_1/dy|_{y=0}$ for p, $\Lambda, \pi$(combined from $\pi^{\pm}$), K(combined from $K^{\pm}$ and $K_S^0$), $\phi$ and $\Xi^−$, and (bottom panel) elliptic flow $v_2$ for p, $\pi$(combined from $\pi^{\pm}$) in heavy- ion collisions. Collision centrality for all data from RHIC is 10-40%, except for 4.5 GeV where 10-30% is for $dv_1/dy|_{y=0}$ and 0-30% is for $v_2$. Statistical and systematic uncertainties are shown as bars and gray bands, respectively. Some uncertainties are smaller than the data points. The JAM and UrQMD results are shown as colored bands:golden, red and blue bands stand for JAM mean-field, UrQMD mean-field and UrQMD cascade mode, respectively. For clarity the x-axis value of the data points have been shifted.

Collision energy dependence of (top panel) directed flow slope $dv_1/dy|_{y=0}$ for p, $\Lambda, \pi$(combined from $\pi^{\pm}$), K(combined from $K^{\pm}$ and $K_S^0$), $\phi$ and $\Xi^−$, and (bottom panel) elliptic flow $v_2$ for p, $\pi$(combined from $\pi^{\pm}$) in heavy- ion collisions. Collision centrality for all data from RHIC is 10-40%, except for 4.5 GeV where 10-30% is for $dv_1/dy|_{y=0}$ and 0-30% is for $v_2$. Statistical and systematic uncertainties are shown as bars and gray bands, respectively. Some uncertainties are smaller than the data points. The JAM and UrQMD results are shown as colored bands:golden, red and blue bands stand for JAM mean-field, UrQMD mean-field and UrQMD cascade mode, respectively. For clarity the x-axis value of the data points have been shifted.

Collision energy dependence of (top panel) directed flow slope $dv_1/dy|_{y=0}$ for p, $\Lambda, \pi$(combined from $\pi^{\pm}$), K(combined from $K^{\pm}$ and $K_S^0$), $\phi$ and $\Xi^−$, and (bottom panel) elliptic flow $v_2$ for p, $\pi$(combined from $\pi^{\pm}$) in heavy- ion collisions. Collision centrality for all data from RHIC is 10-40%, except for 4.5 GeV where 10-30% is for $dv_1/dy|_{y=0}$ and 0-30% is for $v_2$. Statistical and systematic uncertainties are shown as bars and gray bands, respectively. Some uncertainties are smaller than the data points. The JAM and UrQMD results are shown as colored bands:golden, red and blue bands stand for JAM mean-field, UrQMD mean-field and UrQMD cascade mode, respectively. For clarity the x-axis value of the data points have been shifted.

Collision energy dependence of (top panel) directed flow slope $dv_1/dy|_{y=0}$ for p, $\Lambda, \pi$(combined from $\pi^{\pm}$), K(combined from $K^{\pm}$ and $K_S^0$), $\phi$ and $\Xi^−$, and (bottom panel) elliptic flow $v_2$ for p, $\pi$(combined from $\pi^{\pm}$) in heavy- ion collisions. Collision centrality for all data from RHIC is 10-40%, except for 4.5 GeV where 10-30% is for $dv_1/dy|_{y=0}$ and 0-30% is for $v_2$. Statistical and systematic uncertainties are shown as bars and gray bands, respectively. Some uncertainties are smaller than the data points. The JAM and UrQMD results are shown as colored bands:golden, red and blue bands stand for JAM mean-field, UrQMD mean-field and UrQMD cascade mode, respectively. For clarity the x-axis value of the data points have been shifted.

The centrality dependence of Global $\Lambda$-hyperon Polarization at $\sqrt{s_{\rm NN}}=3$ GeV.

The $p_{\rm T}$ dependence of Global $\Lambda$-hyperon Polarization at $\sqrt{s_{\rm NN}}=3$ GeV.

The rapidity dependence of Global $\Lambda$-hyperon Polarization at $\sqrt{s_{\rm NN}}=3$ GeV.

Correlation between the Wilson coefficients (in %), after the 5D fit to data.

The measured differential branching fractions as a function of the invariant hadronic mass squared of the $X_u$ system ($M_X^2$).

The measured differential branching fractions as a function of the light-cone momenta of the hadronic $X_u$ system [$P_+ = (E_X^B - |old{p}_X^B|)$].

The measured differential branching fractions as a function of the light-cone momenta of the hadronic $X_u$ system [$P_- = (E_X^B + |old{p}_X^B|)$].

The background-subtracted yields as a function of $E_\ell^B$.

The background-subtracted yields as a function of $q^2$.

The background-subtracted yields as a function of $M_X$.

The background-subtracted yields as a function of $M_X^2$.

The background-subtracted yields as a function of $P_+$. [$P_+ = (E_X^B - |P_X^B|)$]

The background-subtracted yields as a function of $P_-$. [$P_- = (E_X^B + |P_X^B|)$].

The full experimental correlation matrix for the background-subtracted spectrum of the lepton energy in the $B$ rest frame ($E_\ell^B$).

The full experimental correlation matrix for the background-subtracted spectrum of $q^2$).

The full experimental correlation matrix for the background-subtracted spectrum of $M_X$.

The full experimental correlation matrix for the background-subtracted spectrum of $M_X^2$.

The full experimental correlation matrix for the background-subtracted spectrum of $P_+$.

The full experimental correlation matrix for the background-subtracted spectrum of $P_-$.

Migration matrix of $E_\ell^B$ [in %].

Migration matrix of $q^2$ [in %].

Migration matrix of $M_X$ [in %].

Migration matrix of $M_X^2$ [in %].

Migration matrix of $P_+$ [in %].

Migration matrix of $P_-$ [in %].

The total correction factors and phase space acceptance as a function of the invariant hadronic mass of the $X_u$ system ($M_X$).

The total correction factors and phase space acceptance as a function of the invariant hadronic mass squared of the $X_u$ system ($M_X^2$).

The total correction factors and phase space acceptance as a function of the lepton energy in the $B$ rest frame ($E_\ell^B$).

The total correction factors and phase space acceptance as a function of the four-momentum-transfer squared of the $B$ to the $X_u$ system ($q^2$).

The total correction factors and phase space acceptance as a function of $P_+$.

The total correction factors and phase space acceptance as a function of $P_-$.

The statistical correlations of the differential branching fractions are shown. The matrix elements are ordered for $M_{X}$, $M_{X}^{2}$, $q^{2}$, $E_{\ell}^{B}$, $P_{+}$ and $P_{-}$.

The full experimental (statistical and systematical) correlations of the differential branching fractions are shown. The matrix elements are ordered for $M_{X}$, $M_{X}^{2}$, $q^{2}$, $E_{\ell}^{B}$, $P_{+}$ and $P_{-}$.

The total partial branching fraction with $E_{\ell}^{B} > 1$ GeV. The order of entries is: the 2D fit result of Phys. Rev. D 104, 012008 (2021), the results calcuated with the differential branching fractions of $M_{X}$, $M_{X}^{2}$, $q^{2}$, $E_{\ell}^{B}$, $P_{+}$ and $P_{-}$

The full experimental correlations between the total partial branching fractions from summing the individual bins are shown. The matrix elements are saved in the order of $M_{X}$, $M_{X}^{2}$, $q^{2}$, $E_{\ell}^{B}$, $P_{+}$ and $P_{-}$.

The first moment of the measured differential branching fraction of the lepton energy in the $B$ rest frame ($E_\ell^B$).

The second moment of the measured differential branching fraction of the lepton energy in the $B$ rest frame ($E_\ell^B$).

The third moment of the measured differential branching fraction of the lepton energy in the $B$ rest frame ($E_\ell^B$).

The first moment of the measured differential branching fraction of $q^2$.

The second moment of the measured differential branching fraction of $q^2$.

The third moment of the measured differential branching fraction of $q^2$.

The first moment of the measured differential branching fraction of $M_{X}$.

The second moment of the measured differential branching fraction of $M_{X}$.

The third moment of the measured differential branching fraction of $M_{X}$.

The first moment of the measured differential branching fraction of $P_{+}$.

The second moment of the measured differential branching fraction of $P_{+}$.

The third moment of the measured differential branching fraction of $P_{+}$.

The first moment of the measured differential branching fraction of $P_{-}$.

The second moment of the measured differential branching fraction of $P_{-}$.

The third moment of the measured differential branching fraction of $P_{-}$.

The matrix elements are saved in the order of $M_{X}$, $q^{2}$, $E_{\ell}^{B}$, $P_{+}$ and $P_{-}$. For each variable, the entries is ordered for the first, second and third moments.

Differential signal yields for various signal hypotheses.

Differential signal yields for various signal hypotheses.

Differential signal yields for various signal hypotheses.

Differential signal yields for various signal hypotheses.

Differential signal yields for various signal hypotheses.

Background and data yields in the control and signal region bins. The prediction before ("prefit") and after the background only fit ("b-only") are given separately.

Background and data yields in the control and signal region bins. The prediction before ("prefit") and after the background only fit ("b-only") are given separately.

Background and data yields in the control and signal region bins. The prediction before ("prefit") and after the background only fit ("b-only") are given separately.

Matrix of covariance coefficients between signal region bins. The coefficients are obtained from the background-only fit to the control regions, and serve as input to the simplified likelihood reinterpretation scheme.

Background prediction and observed data yields in the signal region bins. The background yields are obtained from the background-only fit to the corresponding control regions, and serve as input to the simplified likelihood reinterpretation scheme.

Matrix of covariance coefficients between signal region bins. The coefficients are obtained from the background-only fit to the control regions, and serve as input to the simplified likelihood reinterpretation scheme.

Background prediction and observed data yields in the signal region bins. The background yields are obtained from the background-only fit to the corresponding control regions, and serve as input to the simplified likelihood reinterpretation scheme.

Matrix of covariance coefficients between signal region bins. The coefficients are obtained from the background-only fit to the control regions, and serve as input to the simplified likelihood reinterpretation scheme.

Background prediction and observed data yields in the signal region bins. The background yields are obtained from the background-only fit to the corresponding control regions, and serve as input to the simplified likelihood reinterpretation scheme.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Median Expected exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with axial couplings.

Observed exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with axial couplings.

Expected plus 1 s.d. exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with axial couplings.

Expected minus 1 s.d. exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with axial couplings.

Median Expected exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with vector couplings.

Observed exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with vector couplings.

Expected plus 1 s.d. exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with vector couplings.

Expected minus 1 s.d. exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with vector couplings.

Upper limits on the coupling $g_{\chi}$ in the simplified model with a axial mediator.

Upper limits on the coupling $g_{q}$ in the simplified model with a axial mediator.

Upper limits on the coupling $g_{\chi}$ in the simplified model with a vector mediator.

Upper limits on the coupling $g_{q}$ in the simplified model with a vector mediator.

Exclusion limits on the signal strength in the simplified model with scalar couplings.

Exclusion limits on the signal strength in the simplified model with pseudoscalar couplings.

Exclusion limits on the fundamental Planck scale $M_{D}$ as a function of the number of extra dimensions $d$.

Median Expected exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the fermion portal model.

Observed exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the fermion portal model.

Expected plus 1 s.d. exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the fermion portal model.

Expected minus 1 s.d. exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the fermion portal model.

Tagging efficiency for AK8 jets. The efficiency includes the effect of the machine-learning based DeepAK8 tagger, as well as the application of the mass window requirement on the jet. The efficiency is split depending on the matching generator-level object. For reinterpretation purposes, this efficiency can directly be applied to any AK8 jet that is matched to a given type of generator-level object, with no prior selection on the jet mass. Other acceptance requirements on jet $\p_{T}$ and $\eta$ should still be applied.