Distributions of reconstructed VLQ mass for expected postfit background (blue histogram), signal plus background (colored lines), and observed data (black points) for events in the hadronic 5-jet bHbH channel.

Distributions of reconstructed VLQ mass for expected postfit background (blue histogram), signal plus background (colored lines), and observed data (black points) for events in the hadronic 5-jet bHbZ channel.

Distributions of reconstructed VLQ mass for expected postfit background (blue histogram), signal plus background (colored lines), and observed data (black points) for events in the hadronic 5-jet bZbZ channel.

Distributions of reconstructed VLQ mass for expected postfit background (blue histogram), signal plus background (colored lines), and observed data (black points) for events in the hadronic 5-jet bHtW channel.

Distributions of reconstructed VLQ mass for expected postfit background (blue histogram), signal plus background (colored lines), and observed data (black points) for events in the hadronic 5-jet bZtW channel.

Distributions of reconstructed VLQ mass for expected postfit background (blue histogram), signal plus background (colored lines), and observed data (black points) for events in the hadronic 6-jet bHbH channel.

Distributions of reconstructed VLQ mass for expected postfit background (blue histogram), signal plus background (colored lines), and observed data (black points) for events in the hadronic 6-jet bHbZ channel.

Distributions of reconstructed VLQ mass for expected postfit background (blue histogram), signal plus background (colored lines), and observed data (black points) for events in the hadronic 6-jet bZbZ channel.

Distributions of reconstructed VLQ mass for expected postfit background (blue histogram), signal plus background (colored lines), and observed data (black points) for events in the hadronic 6-jet bHtW channel.

Distributions of reconstructed VLQ mass for expected postfit background (blue histogram), signal plus background (colored lines), and observed data (black points) for events in the hadronic 6-jet bZtW channel.

Distributions of reconstructed VLQ mass for expected postfit background (blue histogram), signal plus background (colored lines), and observed data (black points) for events in the semileptonic 3-jet bHbZ channel.

Distributions of reconstructed VLQ mass for expected postfit background (blue histogram), signal plus background (colored lines), and observed data (black points) for events in the semileptonic 3-jet bZbZ channel.

Distributions of reconstructed VLQ mass for expected postfit background (blue histogram), signal plus background (colored lines), and observed data (black points) for events in the semileptonic 4-jet bHbZ channel.

Distributions of reconstructed VLQ mass for expected postfit background (blue histogram), signal plus background (colored lines), and observed data (black points) for events in the semileptonic 4-jet bZbZ channel.

The limit at 95% CL on the cross section for VLQ pair production for the branching fraction hypothesis 0% $\mathcal{B}(B \to bH)$, 100% $\mathcal{B}(B \to bH)$, and 0% $\mathcal{B}(B \to bH)$

The limit at 95% CL on the cross section for VLQ pair production for the branching fraction hypothesis 25% $\mathcal{B}(B \to bH)$, 25% $\mathcal{B}(B \to bH)$, and 50% $\mathcal{B}(B \to bH)$

The limit at 95% CL on the cross section for VLQ pair production for the branching fraction hypothesis 50% $\mathcal{B}(B \to bH)$, 50% $\mathcal{B}(B \to bH)$, and 0% $\mathcal{B}(B \to bH)$

The limit at 95% CL on the cross section for VLQ pair production for the branching fraction hypothesis 100% $\mathcal{B}(B \to bH)$, 0% $\mathcal{B}(B \to bH)$, and 0% $\mathcal{B}(B \to bH)$

Median expected exclusion limits on the VLQ mass at 95% CL as a function of the branching fractions $\mathcal{B}(B \to bH)$ and $\mathcal{B}(B \to tW)$, with $\mathcal{B}(B \to tW) = 1 - \mathcal{B}(B \to bH) - \mathcal{B}(B \to bZ)$. The grey area corresponds to the region where the exclusion limit is less than 1000 GeV.

Median observed exclusion limits on the VLQ mass at 95% CL as a function of the branching fractions $\mathcal{B}(B \to bH)$ and $\mathcal{B}(B \to tW)$, with $\mathcal{B}(B \to tW) = 1 - \mathcal{B}(B \to bH) - \mathcal{B}(B \to bZ)$. The grey area corresponds to the region where the exclusion limit is less than 1000 GeV.

Unfolded E2C distributions in data compared to MC predictions.

Unfolded E2C distributions in data compared to MC predictions.

Unfolded E2C distributions in data compared to MC predictions.

Unfolded E2C distributions in data compared to MC predictions.

Unfolded E2C distributions in data compared to MC predictions.

Unfolded E3C distributions in data compared to MC predictions.

Unfolded E3C distributions in data compared to MC predictions.

Unfolded E3C distributions in data compared to MC predictions.

Unfolded E3C distributions in data compared to MC predictions.

Unfolded E3C distributions in data compared to MC predictions.

Unfolded E3C distributions in data compared to MC predictions.

Unfolded E3C distributions in data compared to MC predictions.

Unfolded E3C distributions in data compared to MC predictions.

Unfolded E3C/E2C distributions in data compared to NLO+NNLL_approx predictions. Theoretial uncertainty in each bin is handled fully correlated as shape uncertainty. For the one-sided uncertainties, we symmetrize them when performing the fit.

Unfolded E3C/E2C distributions in data compared to NLO+NNLL_approx predictions. Theoretial uncertainty in each bin is handled fully correlated as shape uncertainty. For the one-sided uncertainties, we symmetrize them when performing the fit.

Unfolded E3C/E2C distributions in data compared to NLO+NNLL_approx predictions. Theoretial uncertainty in each bin is handled fully correlated as shape uncertainty. For the one-sided uncertainties, we symmetrize them when performing the fit.

Unfolded E3C/E2C distributions in data compared to NLO+NNLL_approx predictions. Theoretial uncertainty in each bin is handled fully correlated as shape uncertainty. For the one-sided uncertainties, we symmetrize them when performing the fit.

Unfolded E3C/E2C distributions in data compared to NLO+NNLL_approx predictions. Theoretial uncertainty in each bin is handled fully correlated as shape uncertainty. For the one-sided uncertainties, we symmetrize them when performing the fit.

Unfolded E3C/E2C distributions in data compared to NLO+NNLL_approx predictions. Theoretial uncertainty in each bin is handled fully correlated as shape uncertainty. For the one-sided uncertainties, we symmetrize them when performing the fit.

Unfolded E3C/E2C distributions in data compared to NLO+NNLL_approx predictions. Theoretial uncertainty in each bin is handled fully correlated as shape uncertainty. For the one-sided uncertainties, we symmetrize them when performing the fit.

Unfolded E3C/E2C distributions in data compared to NLO+NNLL_approx predictions. Theoretial uncertainty in each bin is handled fully correlated as shape uncertainty. For the one-sided uncertainties, we symmetrize them when performing the fit.

The fitted slopes of the E3C/E2C data distributions as a function of jet pt are used to illustrate the dependency of alphas on jet pt.

Unfolded E3C/E2C distributions in data compared to MC predictions.

Unfolded E3C/E2C distributions in data compared to MC predictions.

Unfolded E3C/E2C distributions in data compared to MC predictions.

Unfolded E3C/E2C distributions in data compared to MC predictions.

Unfolded E3C/E2C distributions in data compared to MC predictions.

Unfolded E3C/E2C distributions in data compared to MC predictions.

Unfolded E3C/E2C distributions in data compared to MC predictions.

Unfolded E3C/E2C distributions in data compared to MC predictions.

The chi2 scan result using eq.3 for different alphas.

The correlation matrix is composed by 10 jet pt region, each region is represented by a block in the plot. Inside each block, there are 22 xL bins same as the E2C, E3C and E3C/E2C distributions. Therefore, the x and y bins of the correlation matrix is given by, binNumber = pT_index * 22 + xL_index.

The correlation matrix is composed by 10 jet pt region, each region is represented by a block in the plot. Inside each block, there are 22 xL bins same as the E2C, E3C and E3C/E2C distributions. Therefore, the x and y bins of the correlation matrix is given by, binNumber = pT_index * 22 + xL_index.

The correlation matrix is composed by 10 jet pt region, each region is represented by a block in the plot. Inside each block, there are 22 xL bins same as the E2C, E3C and E3C/E2C distributions. Therefore, the x and y bins of the correlation matrix is given by, binNumber = pT_index * 22 + xL_index.

The energy weight of E2C as defined in eq.1 in the paper is used in the unfolding, the binning is listed in this table.

The energy weight of E3C as defined in eq.1 in the paper is used in the unfolding, the binning is listed in this table.

Observed upper limits at 95% CL on B($\text{H} \rightarrow \text{a}_{1}\text{a}_{1}$) in percent, obtained from the combination of the $\mu\mu$bb and $\tau\tau$bb channels. The results are obtained as functions of $m_{\text{a}_{1}}$ for 2HDM+S Type I (independent of tan$\beta$), Type II (tan$\beta$=2.0), Type III (tan$\beta$=2.0), and Type IV (tan$\beta$=0.6), respectively.

$N_{Lund}, k_t \geq 0.5~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$, Inclusive $\eta$

$N_{Lund}, k_t \geq 0.5~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$, Inclusive $\eta$

$N_{Lund}, k_t \geq 0.5~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$, Inclusive $\eta$

$N_{Lund}, k_t \geq 0.5~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$, Inclusive $\eta$

$N_{Lund}^{Primary}, k_t \geq 0.5~\text{GeV}$, All $p_T$ bins, Central $\eta$

$N_{Lund}^{Primary}, k_t \geq 0.5~\text{GeV}$, All $p_T$ bins, Forward $\eta$

$N_{Lund}^{Primary}, k_t \geq 0.5~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$, Inclusive $\eta$

$N_{Lund}^{Primary}, k_t \geq 0.5~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$, Inclusive $\eta$

$N_{Lund}^{Primary}, k_t \geq 0.5~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$, Inclusive $\eta$

$N_{Lund}^{Primary}, k_t \geq 0.5~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$, Inclusive $\eta$

$N_{Lund}^{Primary}, k_t \geq 0.5~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$, Inclusive $\eta$

$N_{Lund}, k_t \geq 1.0~\text{GeV}$, All $p_T$ bins, Central $\eta$

$N_{Lund}, k_t \geq 1.0~\text{GeV}$, All $p_T$ bins, Forward $\eta$

$N_{Lund}, k_t \geq 1.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$, Inclusive $\eta$

$N_{Lund}, k_t \geq 1.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$, Inclusive $\eta$

$N_{Lund}, k_t \geq 1.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$, Inclusive $\eta$

$N_{Lund}, k_t \geq 1.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$, Inclusive $\eta$

$N_{Lund}, k_t \geq 1.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$, Inclusive $\eta$

$N_{Lund}^{Primary}, k_t \geq 1.0~\text{GeV}$, All $p_T$ bins, Central $\eta$

$N_{Lund}^{Primary}, k_t \geq 1.0~\text{GeV}$, All $p_T$ bins, Forward $\eta$

$N_{Lund}^{Primary}, k_t \geq 1.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$, Inclusive $\eta$

$N_{Lund}^{Primary}, k_t \geq 1.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$, Inclusive $\eta$

$N_{Lund}^{Primary}, k_t \geq 1.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$, Inclusive $\eta$

$N_{Lund}^{Primary}, k_t \geq 1.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$, Inclusive $\eta$

$N_{Lund}^{Primary}, k_t \geq 1.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$, Inclusive $\eta$

$N_{Lund}, k_t \geq 2.0~\text{GeV}$, All $p_T$ bins, Central $\eta$

$N_{Lund}, k_t \geq 2.0~\text{GeV}$, All $p_T$ bins, Forward $\eta$

$N_{Lund}, k_t \geq 2.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$, Inclusive $\eta$

$N_{Lund}, k_t \geq 2.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$, Inclusive $\eta$

$N_{Lund}, k_t \geq 2.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$, Inclusive $\eta$

$N_{Lund}, k_t \geq 2.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$, Inclusive $\eta$

$N_{Lund}, k_t \geq 2.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$, Inclusive $\eta$

$N_{Lund}^{Primary}, k_t \geq 2.0~\text{GeV}$, All $p_T$ bins, Central $\eta$

$N_{Lund}^{Primary}, k_t \geq 2.0~\text{GeV}$, All $p_T$ bins, Forward $\eta$

$N_{Lund}^{Primary}, k_t \geq 2.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$, Inclusive $\eta$

$N_{Lund}^{Primary}, k_t \geq 2.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$, Inclusive $\eta$

$N_{Lund}^{Primary}, k_t \geq 2.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$, Inclusive $\eta$

$N_{Lund}^{Primary}, k_t \geq 2.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$, Inclusive $\eta$

$N_{Lund}^{Primary}, k_t \geq 2.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$, Inclusive $\eta$

$N_{Lund}, k_t \geq 5.0~\text{GeV}$, All $p_T$ bins, Central $\eta$

$N_{Lund}, k_t \geq 5.0~\text{GeV}$, All $p_T$ bins, Forward $\eta$

$N_{Lund}, k_t \geq 5.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$, Inclusive $\eta$

$N_{Lund}, k_t \geq 5.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$, Inclusive $\eta$

$N_{Lund}, k_t \geq 5.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$, Inclusive $\eta$

$N_{Lund}, k_t \geq 5.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$, Inclusive $\eta$

$N_{Lund}, k_t \geq 5.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$, Inclusive $\eta$

$N_{Lund}^{Primary}, k_t \geq 5.0~\text{GeV}$, All $p_T$ bins, Central $\eta$

$N_{Lund}^{Primary}, k_t \geq 5.0~\text{GeV}$, All $p_T$ bins, Forward $\eta$

$N_{Lund}^{Primary}, k_t \geq 5.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$, Inclusive $\eta$

$N_{Lund}^{Primary}, k_t \geq 5.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$, Inclusive $\eta$

$N_{Lund}^{Primary}, k_t \geq 5.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$, Inclusive $\eta$

$N_{Lund}^{Primary}, k_t \geq 5.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$, Inclusive $\eta$

$N_{Lund}^{Primary}, k_t \geq 5.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$, Inclusive $\eta$

$N_{Lund}, k_t \geq 10.0~\text{GeV}$, All $p_T$ bins, Central $\eta$

$N_{Lund}, k_t \geq 10.0~\text{GeV}$, All $p_T$ bins, Forward $\eta$

$N_{Lund}, k_t \geq 10.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$, Inclusive $\eta$

$N_{Lund}, k_t \geq 10.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$, Inclusive $\eta$

$N_{Lund}, k_t \geq 10.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$, Inclusive $\eta$

$N_{Lund}, k_t \geq 10.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$, Inclusive $\eta$

$N_{Lund}, k_t \geq 10.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$, Inclusive $\eta$

$N_{Lund}^{Primary}, k_t \geq 10.0~\text{GeV}$, All $p_T$ bins, Central $\eta$

$N_{Lund}^{Primary}, k_t \geq 10.0~\text{GeV}$, All $p_T$ bins, Forward $\eta$

$N_{Lund}^{Primary}, k_t \geq 10.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$, Inclusive $\eta$

$N_{Lund}^{Primary}, k_t \geq 10.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$, Inclusive $\eta$

$N_{Lund}^{Primary}, k_t \geq 10.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$, Inclusive $\eta$

$N_{Lund}^{Primary}, k_t \geq 10.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$, Inclusive $\eta$

$N_{Lund}^{Primary}, k_t \geq 10.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$, Inclusive $\eta$

$N_{Lund}, k_t \geq 20.0~\text{GeV}$, All $p_T$ bins, Central $\eta$

$N_{Lund}, k_t \geq 20.0~\text{GeV}$, All $p_T$ bins, Forward $\eta$

$N_{Lund}, k_t \geq 20.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$, Inclusive $\eta$

$N_{Lund}, k_t \geq 20.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$, Inclusive $\eta$

$N_{Lund}, k_t \geq 20.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$, Inclusive $\eta$

$N_{Lund}, k_t \geq 20.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$, Inclusive $\eta$

$N_{Lund}, k_t \geq 20.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$, Inclusive $\eta$

$N_{Lund}^{Primary}, k_t \geq 20.0~\text{GeV}$, All $p_T$ bins, Central $\eta$

$N_{Lund}^{Primary}, k_t \geq 20.0~\text{GeV}$, All $p_T$ bins, Forward $\eta$

$N_{Lund}^{Primary}, k_t \geq 20.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$, Inclusive $\eta$

$N_{Lund}^{Primary}, k_t \geq 20.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$, Inclusive $\eta$

$N_{Lund}^{Primary}, k_t \geq 20.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$, Inclusive $\eta$

$N_{Lund}^{Primary}, k_t \geq 20.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$, Inclusive $\eta$

$N_{Lund}^{Primary}, k_t \geq 20.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$, Inclusive $\eta$

$N_{Lund}, k_t \geq 50.0~\text{GeV}$, All $p_T$ bins, Central $\eta$

$N_{Lund}, k_t \geq 50.0~\text{GeV}$, All $p_T$ bins, Forward $\eta$

$N_{Lund}, k_t \geq 50.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$, Inclusive $\eta$

$N_{Lund}, k_t \geq 50.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$, Inclusive $\eta$

$N_{Lund}, k_t \geq 50.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$, Inclusive $\eta$

$N_{Lund}, k_t \geq 50.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$, Inclusive $\eta$

$N_{Lund}, k_t \geq 50.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$, Inclusive $\eta$

$N_{Lund}^{Primary}, k_t \geq 50.0~\text{GeV}$, All $p_T$ bins, Central $\eta$

$N_{Lund}^{Primary}, k_t \geq 50.0~\text{GeV}$, All $p_T$ bins, Forward $\eta$

$N_{Lund}^{Primary}, k_t \geq 50.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$, Inclusive $\eta$

$N_{Lund}^{Primary}, k_t \geq 50.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$, Inclusive $\eta$

$N_{Lund}^{Primary}, k_t \geq 50.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$, Inclusive $\eta$

$N_{Lund}^{Primary}, k_t \geq 50.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$, Inclusive $\eta$

$N_{Lund}^{Primary}, k_t \geq 50.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$, Inclusive $\eta$

$N_{Lund}, k_t \geq 100.0~\text{GeV}$, All $p_T$ bins, Central $\eta$

$N_{Lund}, k_t \geq 100.0~\text{GeV}$, All $p_T$ bins, Forward $\eta$

$N_{Lund}, k_t \geq 100.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$, Inclusive $\eta$

$N_{Lund}, k_t \geq 100.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$, Inclusive $\eta$

$N_{Lund}, k_t \geq 100.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$, Inclusive $\eta$

$N_{Lund}^{Primary}, k_t \geq 100.0~\text{GeV}$, All $p_T$ bins, Central $\eta$

$N_{Lund}^{Primary}, k_t \geq 100.0~\text{GeV}$, All $p_T$ bins, Forward $\eta$

$N_{Lund}^{Primary}, k_t \geq 100.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$, Inclusive $\eta$

$N_{Lund}^{Primary}, k_t \geq 100.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$, Inclusive $\eta$

$N_{Lund}^{Primary}, k_t \geq 100.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$, Inclusive $\eta$

$\lt N_{Lund} \gt$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$, Inclusive $\eta$

$\lt N_{Lund} \gt$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$, Central $\eta$

$\lt N_{Lund} \gt$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$, Forward $\eta$

$\lt N_{Lund} \gt$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$, Inclusive $\eta$

$\lt N_{Lund} \gt$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$, Central $\eta$

$\lt N_{Lund} \gt$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$, Forward $\eta$

$\lt N_{Lund} \gt$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$, Inclusive $\eta$

$\lt N_{Lund} \gt$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$, Central $\eta$

$\lt N_{Lund} \gt$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$, Forward $\eta$

$\lt N_{Lund} \gt$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$, Inclusive $\eta$

$\lt N_{Lund} \gt$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$, Central $\eta$

$\lt N_{Lund} \gt$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$, Forward $\eta$

$\lt N_{Lund} \gt$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$, Inclusive $\eta$

$\lt N_{Lund} \gt$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$, Central $\eta$

$\lt N_{Lund} \gt$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$, Forward $\eta$

$\lt N_{Lund}^{Primary} \gt$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$, Inclusive $\eta$

$\lt N_{Lund}^{Primary} \gt$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$, Central $\eta$

$\lt N_{Lund}^{Primary} \gt$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$, Forward $\eta$

$\lt N_{Lund}^{Primary} \gt$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$, Inclusive $\eta$

$\lt N_{Lund}^{Primary} \gt$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$, Central $\eta$

$\lt N_{Lund}^{Primary} \gt$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$, Forward $\eta$

$\lt N_{Lund}^{Primary} \gt$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$, Inclusive $\eta$

$\lt N_{Lund}^{Primary} \gt$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$, Central $\eta$

$\lt N_{Lund}^{Primary} \gt$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$, Forward $\eta$

$\lt N_{Lund}^{Primary} \gt$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$, Inclusive $\eta$

$\lt N_{Lund}^{Primary} \gt$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$, Central $\eta$

$\lt N_{Lund}^{Primary} \gt$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$, Forward $\eta$

$\lt N_{Lund}^{Primary} \gt$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$, Inclusive $\eta$

$\lt N_{Lund}^{Primary} \gt$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$, Central $\eta$

$\lt N_{Lund}^{Primary} \gt$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$, Forward $\eta$

Inclusive $\lt N_{Lund} \gt$

Inclusive $\lt N_{Lund}^{Primary} \gt$

Data Stat. Covariance, $N_{Lund}, k_t \geq 0.5~\text{GeV}$, All $p_T$ bins

Data Stat. Covariance, $N_{Lund}, k_t \geq 0.5~\text{GeV}$, All $p_T$ bins

Data Stat. Covariance, $N_{Lund}, k_t \geq 0.5~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$

Data Stat. Covariance, $N_{Lund}, k_t \geq 0.5~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$

Data Stat. Covariance, $N_{Lund}, k_t \geq 0.5~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$

Data Stat. Covariance, $N_{Lund}, k_t \geq 0.5~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$

Data Stat. Covariance, $N_{Lund}, k_t \geq 0.5~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$

MC Stat. Covariance, $N_{Lund}, k_t \geq 0.5~\text{GeV}$, All $p_T$ bins

MC Stat. Covariance, $N_{Lund}, k_t \geq 0.5~\text{GeV}$, All $p_T$ bins

MC Stat. Covariance, $N_{Lund}, k_t \geq 0.5~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$

MC Stat. Covariance, $N_{Lund}, k_t \geq 0.5~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$

MC Stat. Covariance, $N_{Lund}, k_t \geq 0.5~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$

MC Stat. Covariance, $N_{Lund}, k_t \geq 0.5~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$

MC Stat. Covariance, $N_{Lund}, k_t \geq 0.5~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$

Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 0.5~\text{GeV}$, All $p_T$ bins

Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 0.5~\text{GeV}$, All $p_T$ bins

Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 0.5~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$

Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 0.5~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$

Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 0.5~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$

Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 0.5~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$

Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 0.5~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$

MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 0.5~\text{GeV}$, All $p_T$ bins

MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 0.5~\text{GeV}$, All $p_T$ bins

MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 0.5~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$

MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 0.5~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$

MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 0.5~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$

MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 0.5~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$

MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 0.5~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$

Data Stat. Covariance, $N_{Lund}, k_t \geq 1.0~\text{GeV}$, All $p_T$ bins

Data Stat. Covariance, $N_{Lund}, k_t \geq 1.0~\text{GeV}$, All $p_T$ bins

Data Stat. Covariance, $N_{Lund}, k_t \geq 1.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$

Data Stat. Covariance, $N_{Lund}, k_t \geq 1.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$

Data Stat. Covariance, $N_{Lund}, k_t \geq 1.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$

Data Stat. Covariance, $N_{Lund}, k_t \geq 1.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$

Data Stat. Covariance, $N_{Lund}, k_t \geq 1.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$

MC Stat. Covariance, $N_{Lund}, k_t \geq 1.0~\text{GeV}$, All $p_T$ bins

MC Stat. Covariance, $N_{Lund}, k_t \geq 1.0~\text{GeV}$, All $p_T$ bins

MC Stat. Covariance, $N_{Lund}, k_t \geq 1.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$

MC Stat. Covariance, $N_{Lund}, k_t \geq 1.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$

MC Stat. Covariance, $N_{Lund}, k_t \geq 1.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$

MC Stat. Covariance, $N_{Lund}, k_t \geq 1.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$

MC Stat. Covariance, $N_{Lund}, k_t \geq 1.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$

Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 1.0~\text{GeV}$, All $p_T$ bins

Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 1.0~\text{GeV}$, All $p_T$ bins

Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 1.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$

Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 1.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$

Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 1.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$

Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 1.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$

Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 1.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$

MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 1.0~\text{GeV}$, All $p_T$ bins

MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 1.0~\text{GeV}$, All $p_T$ bins

MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 1.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$

MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 1.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$

MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 1.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$

MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 1.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$

MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 1.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$

Data Stat. Covariance, $N_{Lund}, k_t \geq 2.0~\text{GeV}$, All $p_T$ bins

Data Stat. Covariance, $N_{Lund}, k_t \geq 2.0~\text{GeV}$, All $p_T$ bins

Data Stat. Covariance, $N_{Lund}, k_t \geq 2.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$

Data Stat. Covariance, $N_{Lund}, k_t \geq 2.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$

Data Stat. Covariance, $N_{Lund}, k_t \geq 2.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$

Data Stat. Covariance, $N_{Lund}, k_t \geq 2.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$

Data Stat. Covariance, $N_{Lund}, k_t \geq 2.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$

MC Stat. Covariance, $N_{Lund}, k_t \geq 2.0~\text{GeV}$, All $p_T$ bins

MC Stat. Covariance, $N_{Lund}, k_t \geq 2.0~\text{GeV}$, All $p_T$ bins

MC Stat. Covariance, $N_{Lund}, k_t \geq 2.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$

MC Stat. Covariance, $N_{Lund}, k_t \geq 2.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$

MC Stat. Covariance, $N_{Lund}, k_t \geq 2.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$

MC Stat. Covariance, $N_{Lund}, k_t \geq 2.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$

MC Stat. Covariance, $N_{Lund}, k_t \geq 2.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$

Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 2.0~\text{GeV}$, All $p_T$ bins

Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 2.0~\text{GeV}$, All $p_T$ bins

Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 2.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$

Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 2.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$

Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 2.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$

Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 2.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$

Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 2.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$

MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 2.0~\text{GeV}$, All $p_T$ bins

MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 2.0~\text{GeV}$, All $p_T$ bins

MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 2.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$

MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 2.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$

MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 2.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$

MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 2.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$

MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 2.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$

Data Stat. Covariance, $N_{Lund}, k_t \geq 5.0~\text{GeV}$, All $p_T$ bins

Data Stat. Covariance, $N_{Lund}, k_t \geq 5.0~\text{GeV}$, All $p_T$ bins

Data Stat. Covariance, $N_{Lund}, k_t \geq 5.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$

Data Stat. Covariance, $N_{Lund}, k_t \geq 5.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$

Data Stat. Covariance, $N_{Lund}, k_t \geq 5.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$

Data Stat. Covariance, $N_{Lund}, k_t \geq 5.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$

Data Stat. Covariance, $N_{Lund}, k_t \geq 5.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$

MC Stat. Covariance, $N_{Lund}, k_t \geq 5.0~\text{GeV}$, All $p_T$ bins

MC Stat. Covariance, $N_{Lund}, k_t \geq 5.0~\text{GeV}$, All $p_T$ bins

MC Stat. Covariance, $N_{Lund}, k_t \geq 5.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$

MC Stat. Covariance, $N_{Lund}, k_t \geq 5.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$

MC Stat. Covariance, $N_{Lund}, k_t \geq 5.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$

MC Stat. Covariance, $N_{Lund}, k_t \geq 5.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$

MC Stat. Covariance, $N_{Lund}, k_t \geq 5.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$

Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 5.0~\text{GeV}$, All $p_T$ bins

Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 5.0~\text{GeV}$, All $p_T$ bins

Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 5.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$

Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 5.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$

Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 5.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$

Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 5.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$

Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 5.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$

MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 5.0~\text{GeV}$, All $p_T$ bins

MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 5.0~\text{GeV}$, All $p_T$ bins

MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 5.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$

MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 5.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$

MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 5.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$

MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 5.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$

MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 5.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$

Data Stat. Covariance, $N_{Lund}, k_t \geq 10.0~\text{GeV}$, All $p_T$ bins

Data Stat. Covariance, $N_{Lund}, k_t \geq 10.0~\text{GeV}$, All $p_T$ bins

Data Stat. Covariance, $N_{Lund}, k_t \geq 10.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$

Data Stat. Covariance, $N_{Lund}, k_t \geq 10.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$

Data Stat. Covariance, $N_{Lund}, k_t \geq 10.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$

Data Stat. Covariance, $N_{Lund}, k_t \geq 10.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$

Data Stat. Covariance, $N_{Lund}, k_t \geq 10.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$

MC Stat. Covariance, $N_{Lund}, k_t \geq 10.0~\text{GeV}$, All $p_T$ bins

MC Stat. Covariance, $N_{Lund}, k_t \geq 10.0~\text{GeV}$, All $p_T$ bins

MC Stat. Covariance, $N_{Lund}, k_t \geq 10.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$

MC Stat. Covariance, $N_{Lund}, k_t \geq 10.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$

MC Stat. Covariance, $N_{Lund}, k_t \geq 10.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$

MC Stat. Covariance, $N_{Lund}, k_t \geq 10.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$

MC Stat. Covariance, $N_{Lund}, k_t \geq 10.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$

Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 10.0~\text{GeV}$, All $p_T$ bins

Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 10.0~\text{GeV}$, All $p_T$ bins

Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 10.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$

Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 10.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$

Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 10.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$

Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 10.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$

Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 10.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$

MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 10.0~\text{GeV}$, All $p_T$ bins

MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 10.0~\text{GeV}$, All $p_T$ bins

MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 10.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$

MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 10.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$

MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 10.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$

MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 10.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$

MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 10.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$

Data Stat. Covariance, $N_{Lund}, k_t \geq 20.0~\text{GeV}$, All $p_T$ bins

Data Stat. Covariance, $N_{Lund}, k_t \geq 20.0~\text{GeV}$, All $p_T$ bins

Data Stat. Covariance, $N_{Lund}, k_t \geq 20.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$

Data Stat. Covariance, $N_{Lund}, k_t \geq 20.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$

Data Stat. Covariance, $N_{Lund}, k_t \geq 20.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$

Data Stat. Covariance, $N_{Lund}, k_t \geq 20.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$

Data Stat. Covariance, $N_{Lund}, k_t \geq 20.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$

MC Stat. Covariance, $N_{Lund}, k_t \geq 20.0~\text{GeV}$, All $p_T$ bins

MC Stat. Covariance, $N_{Lund}, k_t \geq 20.0~\text{GeV}$, All $p_T$ bins

MC Stat. Covariance, $N_{Lund}, k_t \geq 20.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$

MC Stat. Covariance, $N_{Lund}, k_t \geq 20.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$

MC Stat. Covariance, $N_{Lund}, k_t \geq 20.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$

MC Stat. Covariance, $N_{Lund}, k_t \geq 20.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$

MC Stat. Covariance, $N_{Lund}, k_t \geq 20.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$

Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 20.0~\text{GeV}$, All $p_T$ bins

Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 20.0~\text{GeV}$, All $p_T$ bins

Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 20.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$

Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 20.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$

Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 20.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$

Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 20.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$

Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 20.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$

MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 20.0~\text{GeV}$, All $p_T$ bins

MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 20.0~\text{GeV}$, All $p_T$ bins

MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 20.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$

MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 20.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$

MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 20.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$

MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 20.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$

MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 20.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$

Data Stat. Covariance, $N_{Lund}, k_t \geq 50.0~\text{GeV}$, All $p_T$ bins

Data Stat. Covariance, $N_{Lund}, k_t \geq 50.0~\text{GeV}$, All $p_T$ bins

Data Stat. Covariance, $N_{Lund}, k_t \geq 50.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$

Data Stat. Covariance, $N_{Lund}, k_t \geq 50.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$

Data Stat. Covariance, $N_{Lund}, k_t \geq 50.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$

Data Stat. Covariance, $N_{Lund}, k_t \geq 50.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$

Data Stat. Covariance, $N_{Lund}, k_t \geq 50.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$

MC Stat. Covariance, $N_{Lund}, k_t \geq 50.0~\text{GeV}$, All $p_T$ bins

MC Stat. Covariance, $N_{Lund}, k_t \geq 50.0~\text{GeV}$, All $p_T$ bins

MC Stat. Covariance, $N_{Lund}, k_t \geq 50.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$

MC Stat. Covariance, $N_{Lund}, k_t \geq 50.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$

MC Stat. Covariance, $N_{Lund}, k_t \geq 50.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$

MC Stat. Covariance, $N_{Lund}, k_t \geq 50.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$

MC Stat. Covariance, $N_{Lund}, k_t \geq 50.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$

Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 50.0~\text{GeV}$, All $p_T$ bins

Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 50.0~\text{GeV}$, All $p_T$ bins

Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 50.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$

Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 50.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$

Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 50.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$

Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 50.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$

Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 50.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$

MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 50.0~\text{GeV}$, All $p_T$ bins

MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 50.0~\text{GeV}$, All $p_T$ bins

MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 50.0~\text{GeV}$, $300~\text{GeV} \leq p_T < 500~\text{GeV}$

MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 50.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$

MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 50.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$

MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 50.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$

MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 50.0~\text{GeV}$, $1250~\text{GeV} \leq p_T < 4500~\text{GeV}$

Data Stat. Covariance, $N_{Lund}, k_t \geq 100.0~\text{GeV}$, All $p_T$ bins

Data Stat. Covariance, $N_{Lund}, k_t \geq 100.0~\text{GeV}$, All $p_T$ bins

Data Stat. Covariance, $N_{Lund}, k_t \geq 100.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$

Data Stat. Covariance, $N_{Lund}, k_t \geq 100.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$

Data Stat. Covariance, $N_{Lund}, k_t \geq 100.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$

MC Stat. Covariance, $N_{Lund}, k_t \geq 100.0~\text{GeV}$, All $p_T$ bins

MC Stat. Covariance, $N_{Lund}, k_t \geq 100.0~\text{GeV}$, All $p_T$ bins

MC Stat. Covariance, $N_{Lund}, k_t \geq 100.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$

MC Stat. Covariance, $N_{Lund}, k_t \geq 100.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$

MC Stat. Covariance, $N_{Lund}, k_t \geq 100.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$

Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 100.0~\text{GeV}$, All $p_T$ bins

Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 100.0~\text{GeV}$, All $p_T$ bins

Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 100.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$

Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 100.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$

Data Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 100.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$

MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 100.0~\text{GeV}$, All $p_T$ bins

MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 100.0~\text{GeV}$, All $p_T$ bins

MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 100.0~\text{GeV}$, $500~\text{GeV} \leq p_T < 750~\text{GeV}$

MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 100.0~\text{GeV}$, $750~\text{GeV} \leq p_T < 1000~\text{GeV}$

MC Stat. Covariance, $N_{Lund}^{Primary}, k_t \geq 100.0~\text{GeV}$, $1000~\text{GeV} \leq p_T < 1250~\text{GeV}$

Observed exclusion limits at the 95% CL in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$ and a $-1 \sigma$ deviation of the NNLO+NNLL theoretical cross-section of a $\tilde{t}_1$ pair-production.

Expected exclusion limits at the 95% CL in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.

The $1\sigma$ variation of expected 95% CL exclusion contour obtained by varying MC statistical uncertainties, detector-related systematic uncertainties, and theoretical uncertainties in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.

The $2\sigma$ variation of expected 95%CL exclusion contour obtained by varying MC statistical uncertainties, detector-related systematic uncertainties, and theoretical uncertainties in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.

Observed exclusion limits at the 95% CL in the $m_{\tilde{t}_1} - $BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1)$ plane, assuming $m_{\tilde\chi^0_1} = 1 \mathrm{GeV}$.

Observed exclusion limits at the 95% CL in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming $m_{\tilde\chi^0_1} = 1 \mathrm{ GeV}$ and a $+1 \sigma$ deviation of the NNLO+NNLL theoretical cross-section of a $\tilde{t}_1$ pair-production.

Observed exclusion limits at the 95% CL in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming $m_{\tilde\chi^0_1} = 1 \mathrm{ GeV}$ and a $-1 \sigma$ deviation of the NNLO+NNLL theoretical cross-section of a $\tilde{t}_1$ pair-production.

Expected exclusion limits at the 95% CL in the $m_{\tilde{t}_1} - $BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1)$ plane, assuming $m_{\tilde\chi^0_1} = 1 \mathrm{GeV}$.

The $1\sigma$ variation of expected 95% CL exclusion contour obtained by varying MC statistical uncertainties, detector-related systematic uncertainties, and theoretical uncertainties in the $m_{\tilde{t}_1} - $BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1)$ plane, assuming $m_{\tilde\chi^0_1} = 1 \mathrm{GeV}$.

The $2\sigma$ variation of expected 95%CL exclusion contour obtained by varying MC statistical uncertainties, detector-related systematic uncertainties, and theoretical uncertainties in the $m_{\tilde{t}_1} - $BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1)$ plane, assuming $m_{\tilde\chi^0_1} = 1 \mathrm{GeV}$.

Observed upper limits on the top-spartner pair production cross-section in fb at the 95% CL in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$

Expected upper limits on the top-spartner pair production cross-section in fb at the 95% CL in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$

Observed upper limits on the top-spartner pair production cross-section in fb at the 95% CL in the $m_{\tilde{t}_1} - $BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1)$ plane, assuming $m_{\tilde\chi^0_1} = 1 \mathrm{GeV}$.

Expected upper limits on the top-spartner pair production cross-section in fb at the 95% CL in the $m_{\tilde{t}_1} - $BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1)$ plane, assuming $m_{\tilde\chi^0_1} = 1 \mathrm{GeV}$.

Post-fit distribution of $N_{\mathrm{tops}}^{\mathrm{DNN}} (\mathrm{R=1.0})$ in the SRA signal region presented without the associated SRA applied to the variable. For each bin yields for the data and total SM prediction are provided. The SM prediction is provided with the total uncertainty, including the MC statistical uncertainty, detector-related systematic uncertainties and theoretical uncertainties. The rightmost bin includes overflow events.

Post-fit distribution of $m_{\mathrm{T2}}(j^{b}_{R=1.0}, c)$ in the SRA signal region presented without the associated SRA applied to the variable. For each bin yields for the data and total SM prediction are provided. The SM prediction is provided with the total uncertainty, including the MC statistical uncertainty, detector-related systematic uncertainties and theoretical uncertainties. The rightmost bin includes overflow events.

Post-fit distribution of $p_{\mathrm{T}}(c_{1})$ in the SRB signal region presented without the associated SRB applied to the variable. For each bin yields for the data and total SM prediction are provided. The SM prediction is provided with the total uncertainty, including the MC statistical uncertainty, detector-related systematic uncertainties and theoretical uncertainties. The rightmost bin includes overflow events.

Post-fit distribution of $m_{\mathrm{T}}(j, \mathrm{E}_{\mathrm{T}}^{\mathrm{miss}})_{\mathrm{close}}$ in the SRB signal region presented without the associated SRB applied to the variable. For each bin yields for the data and total SM prediction are provided. The SM prediction is provided with the total uncertainty, including the MC statistical uncertainty, detector-related systematic uncertainties and theoretical uncertainties. The rightmost bin includes overflow events.

Post-fit distribution of $\mathrm{E}_{\mathrm{T}}^{\mathrm{miss}} \textrm{Significance}$ in the SRC signal region presented without the associated SRC applied to the variable. For each bin yields for the data and total SM prediction are provided. The SM prediction is provided with the total uncertainty, including the MC statistical uncertainty, detector-related systematic uncertainties and theoretical uncertainties. The rightmost bin includes overflow events.

Post-fit distribution of $m_{\mathrm{T}}(j, \mathrm{E}_{\mathrm{T}}^{\mathrm{miss}})_{\mathrm{close}}$ in the SRC signal region presented without the associated SRC applied to the variable. For each bin yields for the data and total SM prediction are provided. The SM prediction is provided with the total uncertainty, including the MC statistical uncertainty, detector-related systematic uncertainties and theoretical uncertainties. The rightmost bin includes overflow events.

Post-fit distribution of NN signal score in the SRD signal region presented without the associated SRD applied to the variable. For each bin yields for the data and total SM prediction are provided. The SM prediction is provided with the total uncertainty, including the MC statistical uncertainty, detector-related systematic uncertainties and theoretical uncertainties. The rightmost bin includes overflow events.

Post-fit distribution of $m_{\mathrm{eff}}$ in the SRD signal region. For each bin yields for the data and total SM prediction are provided. The SM prediction is provided with the total uncertainty, including the MC statistical uncertainty, detector-related systematic uncertainties and theoretical uncertainties. The rightmost bin includes overflow events.

Pull plots showing the SRA, SRB and SRC post-fit data and SM agreement using the background-only fit configuration

Pull plots showing the SRD post-fit data and SM agreement using the background-only fit configuration

Cutflow for the reference point $(m_{\tilde{t}_1}, m_{\tilde\chi^0_1})=$ (900,1) , (700,300), (550,375) in the Signal region A. Results are shown including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$.

Cutflow for the reference point $(m_{\tilde{t}_1}, m_{\tilde\chi^0_1})=$ (900,1) , (700,300), (550,375) in the Signal region B. Results are shown including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$.

Cutflow for the reference point $(m_{\tilde{t}_1}, m_{\tilde\chi^0_1})=$ (900,1) , (700,300), (550,375) in the Signal region C. Results are shown including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$.

Cutflow for the reference point $(m_{\tilde{t}_1}, m_{\tilde\chi^0_1})=$ (900,1) , (700,300), (550,375) in the Signal region D 750. Results are shown including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$.

Cutflow for the reference point $(m_{\tilde{t}_1}, m_{\tilde\chi^0_1})=$ (900,1) , (700,300), (550,375) in the Signal region D 1000. Results are shown including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$.

Cutflow for the reference point $(m_{\tilde{t}_1}, m_{\tilde\chi^0_1})=$ (900,1) , (700,300), (550,375) in the Signal region D 1250. Results are shown including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$.

Cutflow for the reference point $(m_{\tilde{t}_1}, m_{\tilde\chi^0_1})=$ (900,1) , (700,300), (550,375) in the Signal region D 1500. Results are shown including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$.

Cutflow for the reference point $(m_{\tilde{t}_1}, m_{\tilde\chi^0_1})=$ (900,1) , (700,300), (550,375) in the Signal region D 1750. Results are shown including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$.

Cutflow for the reference point $(m_{\tilde{t}_1}, m_{\tilde\chi^0_1})=$ (900,1) , (700,300), (550,375) in the Signal region D 2000. Results are shown including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$.

Signal acceptance in the SRA$^{[450,575]}$ region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$ (a factor of 10 larger than in the plots).

Signal efficiency in the SRA$^{[450,575]}$ region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.

Signal acceptance in the SRA$^{\geq 575}$ region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$ (a factor of 10 larger than in the plots).

Signal efficiency in the SRA$^{\geq 575}$ region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.

Signal acceptance in the SRB$^{[100,150]}$ region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$ (a factor of 10 larger than in the plots).

Signal efficiency in the SRB$^{[100,150]}$ region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.

Signal acceptance in the SRB$^{[150,400]}$ region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$ (a factor of 10 larger than in the plots).

Signal efficiency in the SRB$^{[150,400]}$ region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.

Signal acceptance in the SRB$^{\geq 400}$ region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$ (a factor of 10 larger than in the plots).

Signal efficiency in the SRB$^{\geq 400}$ region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.

Signal acceptance in the SRC$^{[100,150]}$ region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$ (a factor of 10 larger than in the plots).

Signal efficiency in the SRC$^{[100,150]}$ region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.

Signal acceptance in the SRC$^{[150,300]}$ region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$ (a factor of 10 larger than in the plots).

Signal efficiency in the SRC$^{[150,300]}$ region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.

Signal acceptance in the SRC$^{[300,500]}$ region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$ (a factor of 10 larger than in the plots).

Signal efficiency in the SRC$^{[300,500]}$ region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.

Signal acceptance in the SRC$^{\geq 500}$ region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$ (a factor of 10 larger than in the plots).

Signal efficiency in the SRC$^{\geq 500}$ region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.

Signal acceptance in the SRD750 region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$ (a factor of 10 larger than in the plots).

Signal efficiency in the SRD750 region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.

Signal acceptance in the SRD1000 region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$ (a factor of 10 larger than in the plots).

Signal efficiency in the SRD1000 region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.

Signal acceptance in the SRD1250 region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$ (a factor of 10 larger than in the plots).

Signal efficiency in the SRD1250 region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.

Signal acceptance in the SRD1500 region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$ (a factor of 10 larger than in the plots).

Signal efficiency in the SRD1500 region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.

Signal acceptance in the SRD1750 region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$ (a factor of 10 larger than in the plots).

Signal efficiency in the SRD1750 region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.

Signal acceptance in the SRD2000 region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$ (a factor of 10 larger than in the plots).

Signal efficiency in the SRD2000 region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.

Dilepton mass spectra for the high mass $W\phi($ee$)$ SR1 event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.

Dilepton mass spectra for the low mass $W\phi($ee$)$ SR2 event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.

Dilepton mass spectra for the high mass $W\phi($ee$)$ SR2 event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.

Dilepton mass spectra for the low mass $Z\phi($ee$)$ SR event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.

Dilepton mass spectra for the high mass $Z\phi($ee$)$ SR event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.

Dilepton mass spectra for the low mass $t\bar{t}\phi($ee$)$ SR1 event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.

Dilepton mass spectra for the high mass $t\bar{t}\phi($ee$)$ SR1 event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.

Dilepton mass spectra for the low mass $t\bar{t}\phi($ee$)$ SR2 event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.

Dilepton mass spectra for the high mass $t\bar{t}\phi($ee$)$ SR2 event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.

Dilepton mass spectra for the low mass $t\bar{t}\phi($ee$)$ SR3 event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.

Dilepton mass spectra for the high mass $t\bar{t}\phi($ee$)$ SR3 event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.

Dilepton mass spectra for the low mass $W\phi(\mu\mu)$ SR1 event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.

Dilepton mass spectra for the high mass $W\phi(\mu\mu)$ SR1 event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.

Dilepton mass spectra for the low mass $W\phi(\mu\mu)$ SR2 event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.

Dilepton mass spectra for the high mass $W\phi(\mu\mu)$ SR2 event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.

Dilepton mass spectra for the low mass $Z\phi(\mu\mu)$ SR event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.

Dilepton mass spectra for the high mass $Z\phi(\mu\mu)$ SR event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.

Dilepton mass spectra for the low mass $t\bar{t}\phi(\mu\mu)$ SR1 event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.

Dilepton mass spectra for the high mass $t\bar{t}\phi(\mu\mu)$ SR1 event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.

Dilepton mass spectra for the low mass $t\bar{t}\phi(\mu\mu)$ SR2 event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.

Dilepton mass spectra for the high mass $t\bar{t}\phi(\mu\mu)$ SR2 event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.

Dilepton mass spectra for the low mass $t\bar{t}\phi(\mu\mu)$ SR3 event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.

Dilepton mass spectra for the high mass $t\bar{t}\phi(\mu\mu)$ SR3 event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.

Dilepton mass spectra for the $W\phi(\tau\tau)$ SR1 event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The rightmost bin contains the overflow events in each distribution. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.

Dilepton mass spectra for the $Z\phi(\tau\tau)$ SR1 event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The rightmost bin contains the overflow events in each distribution. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.

Dilepton mass spectra for the $W\phi(\tau\tau)$ SR2 event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The rightmost bin contains the overflow events in each distribution. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.

Dilepton mass spectra for the $Z\phi(\tau\tau)$ SR2 event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The rightmost bin contains the overflow events in each distribution. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.

Dilepton mass spectra for the $W\phi(\tau\tau)$ SR3 event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The rightmost bin contains the overflow events in each distribution. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.

Dilepton mass spectra for the $Z\phi(\tau\tau)$ SR3 event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The rightmost bin contains the overflow events in each distribution. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.

Dilepton mass spectra for the $t\bar{t}\phi(\tau\tau)$ SR1 event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The rightmost bin contains the overflow events in each distribution. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.

Dilepton mass spectra for the $t\bar{t}\phi(\tau\tau)$ SR2 event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The rightmost bin contains the overflow events in each distribution. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.

Dilepton mass spectra for the $t\bar{t}\phi(\tau\tau)$ SR3 event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The rightmost bin contains the overflow events in each distribution. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.

Dilepton mass spectra for the $t\bar{t}\phi(\tau\tau)$ SR4 event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The rightmost bin contains the overflow events in each distribution. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.

Dilepton mass spectra for the $t\bar{t}\phi(\tau\tau)$ SR5 event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The rightmost bin contains the overflow events in each distribution. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.

Dilepton mass spectra for the $t\bar{t}\phi(\tau\tau)$ SR6 event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The rightmost bin contains the overflow events in each distribution. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.

Dilepton mass spectra for the $t\bar{t}\phi(\tau\tau)$ SR7 event selections for the combined 2016–2018 data set. The lower panel shows the ratio of observed events to the total expected SM background prediction (Obs/Exp), and the gray band represents the sum of statistical and systematic uncertainties in the background prediction. The rightmost bin contains the overflow events in each distribution. The expected background distributions and the uncertainties are shown after the data is fit under the background-only hypothesis. For illustration, two example signal hypotheses for the production and decay of a scalar and a pseudoscalar $\phi$ boson are shown, and their masses (in units of GeV) are indicated in the legend. The signals are normalized to the product of the cross section and branching fraction of 10 fb.

The 95% confidence level upper limits on the product of the production cross section and branching fraction of the $W\phi$ signal with scalar couplings in the ee decay scenario. The vertical gray band indicates the mass region not considered in the analysis. The red line is the theoretical prediction for the product of the production cross section and branching fraction of the $W\phi$ signal.

The 95% confidence level upper limits on the product of the production cross section and branching fraction of the $W\phi$ signal with pseudoscalar couplings in the ee decay scenario. The vertical gray band indicates the mass region not considered in the analysis. The red line is the theoretical prediction for the product of the production cross section and branching fraction of the $W\phi$ signal.

The 95% confidence level upper limits on the product of the production cross section and branching fraction of the $W\phi$ signal with scalar couplings in the $\mu\mu$ decay scenario. The vertical gray band indicates the mass region not considered in the analysis. The red line is the theoretical prediction for the product of the production cross section and branching fraction of the $W\phi$ signal.

The 95% confidence level upper limits on the product of the production cross section and branching fraction of the $W\phi$ signal with pseudoscalar couplings in the $\mu\mu$ decay scenario. The vertical gray band indicates the mass region not considered in the analysis. The red line is the theoretical prediction for the product of the production cross section and branching fraction of the $W\phi$ signal.

The 95% confidence level upper limits on the product of the production cross section and branching fraction of the $W\phi$ signal with scalar couplings in the $\tau\tau$ decay scenario. The red line is the theoretical prediction for the product of the production cross section and branching fraction of the $W\phi$ signal.

The 95% confidence level upper limits on the product of the production cross section and branching fraction of the $W\phi$ signal with pseudoscalar couplings in the $\tau\tau$ decay scenario. The red line is the theoretical prediction for the product of the production cross section and branching fraction of the $W\phi$ signal.

The 95% confidence level upper limits on the product of the production cross section and branching fraction of the $Z\phi$ signal with scalar couplings in the ee decay scenario. The vertical gray band indicates the mass region not considered in the analysis. The red line is the theoretical prediction for the product of the production cross section and branching fraction of the $Z\phi$ signal.

The 95% confidence level upper limits on the product of the production cross section and branching fraction of the $Z\phi$ signal with pseudoscalar couplings in the ee decay scenario. The vertical gray band indicates the mass region not considered in the analysis. The red line is the theoretical prediction for the product of the production cross section and branching fraction of the $Z\phi$ signal.

The 95% confidence level upper limits on the product of the production cross section and branching fraction of the $Z\phi$ signal with scalar couplings in the $\mu\mu$ decay scenario. The vertical gray band indicates the mass region not considered in the analysis. The red line is the theoretical prediction for the product of the production cross section and branching fraction of the $Z\phi$ signal.

The 95% confidence level upper limits on the product of the production cross section and branching fraction of the $Z\phi$ signal with pseudoscalar couplings in the $\mu\mu$ decay scenario. The vertical gray band indicates the mass region not considered in the analysis. The red line is the theoretical prediction for the product of the production cross section and branching fraction of the $Z\phi$ signal.

The 95% confidence level upper limits on the product of the production cross section and branching fraction of the $Z\phi$ signal with scalar couplings in the $\tau\tau$ decay scenario. The red line is the theoretical prediction for the product of the production cross section and branching fraction of the $Z\phi$ signal.

The 95% confidence level upper limits on the product of the production cross section and branching fraction of the $Z\phi$ signal with pseudoscalar couplings in the $\tau\tau$ decay scenario. The red line is the theoretical prediction for the product of the production cross section and branching fraction of the $Z\phi$ signal.

The 95% confidence level upper limits on the product of the production cross section and branching fraction of the $W\phi$ signal with H-like production in the ee decay scenario. The vertical gray band indicates the mass region not considered in the analysis. The red line is the theoretical prediction for the product of the production cross section and branching fraction of the $W\phi$ signal.

The 95% confidence level upper limits on the product of the production cross section and branching fraction of the $Z\phi$ signal with H-like production in the ee decay scenario. The vertical gray band indicates the mass region not considered in the analysis. The red line is the theoretical prediction for the product of the production cross section and branching fraction of the $Z\phi$ signal.

The 95% confidence level upper limits on the product of the production cross section and branching fraction of the $W\phi$ signal with H-like production in the $\mu\mu$ decay scenario. The vertical gray band indicates the mass region not considered in the analysis. The red line is the theoretical prediction for the product of the production cross section and branching fraction of the $W\phi$ signal.

The 95% confidence level upper limits on the product of the production cross section and branching fraction of the $Z\phi$ signal with H-like production in the $\mu\mu$ decay scenario. The vertical gray band indicates the mass region not considered in the analysis. The red line is the theoretical prediction for the product of the production cross section and branching fraction of the $Z\phi$ signal.

The 95% confidence level upper limits on the product of the production cross section and branching fraction of the $W\phi$ signal with H-like production in the $\tau\tau$ decay scenario. The red line is the theoretical prediction for the product of the production cross section and branching fraction of the $W\phi$ signal.

The 95% confidence level upper limits on the product of the production cross section and branching fraction of the $Z\phi$ signal with H-like production in the $\tau\tau$ decay scenario. The red line is the theoretical prediction for the product of the production cross section and branching fraction of the $Z\phi$ signal.

The 95% confidence level upper limits on the product of the production cross section and branching fraction of the $t\bar{t} \phi$ signal with scalar couplings in the ee decay scenario. The vertical gray band indicates the mass region not considered in the analysis. The red line is the theoretical prediction for the product of the production cross section and branching fraction of the $t\bar{t} \phi$ signal.

The 95% confidence level upper limits on the product of the production cross section and branching fraction of the $t\bar{t} \phi$ signal with pseudoscalar couplings in the ee decay scenario. The vertical gray band indicates the mass region not considered in the analysis. The red line is the theoretical prediction for the product of the production cross section and branching fraction of the $t\bar{t} \phi$ signal.

The 95% confidence level upper limits on the product of the production cross section and branching fraction of the $t\bar{t} \phi$ signal with scalar couplings in the $\mu\mu$ decay scenario. The vertical gray band indicates the mass region not considered in the analysis. The red line is the theoretical prediction for the product of the production cross section and branching fraction of the $t\bar{t} \phi$ signal.

The 95% confidence level upper limits on the product of the production cross section and branching fraction of the $t\bar{t} \phi$ signal with pseudoscalar couplings in the $\mu\mu$ decay scenario. The vertical gray band indicates the mass region not considered in the analysis. The red line is the theoretical prediction for the product of the production cross section and branching fraction of the $t\bar{t} \phi$ signal.

The 95% confidence level upper limits on the product of the production cross section and branching fraction of the $t\bar{t} \phi$ signal with scalar couplings in the $\tau\tau$ decay scenario. The red line is the theoretical prediction for the product of the production cross section and branching fraction of the $t\bar{t} \phi$ signal.

The 95% confidence level upper limits on the product of the production cross section and branching fraction of the $t\bar{t} \phi$ signal with pseudoscalar couplings in the $\tau\tau$ decay scenario. The red line is the theoretical prediction for the product of the production cross section and branching fraction of the $t\bar{t} \phi$ signal.

The 95% confidence level upper limits on $g^2_{tS}$ for the dilaton-like $t\bar{t} \phi$ signal model. Masses of the $\phi$ boson above 300 GeV are not probed for the dilaton-like signal model as the $\phi$ branching fraction into top quark-antiquark pairs becomes nonnegligible.

The 95% confidence level upper limits on $g^2_{tPS}$ for the axion-like $t\bar{t} \phi$ signal model. Masses of the $\phi$ boson above 300 GeV are not probed for the axion-like signal model as the $\phi$ branching fraction into top quark-antiquark pairs becomes nonnegligible.

The 95% confidence level upper limits on the product of $sin^2 \theta$ and branching fraction for the H-like production of X$\phi \rightarrow$ ee. The vertical gray band indicates the mass region not considered in the analysis.

The 95% confidence level upper limits on the product of $sin^2 \theta$ and branching fraction for the H-like production of X$\phi \rightarrow \mu\mu$. The vertical gray band indicates the mass region not considered in the analysis.

The 95% confidence level upper limits on $sin^2 \theta$ for the H-like production and decay of X$\phi$ signal model.

Cross section in units of pb for the W$\phi$, Z$\phi$, and $t\bar{t}\phi$ signals as a function of the $\phi$ boson mass in GeV. All cross sections are inclusive of all W, Z, $t\bar{t}$ and $\phi$ decay modes.

The 95% confidence level expected and observed upper limits on the product of $g^{2}_{tS}$ and $\bf{\it{B}}(\phi \rightarrow $ee$)$ of the $t\bar{t} \phi$ signal with scalar couplings, where $g_{tS}$ denotes the coupling of the $\phi$ boson to the top quark and $\bf{\it{B}}(\phi \rightarrow $ee$)$ is the branching fraction of the $\phi$ boson into an electron pair. The vertical gray band indicates the mass region not considered in the analysis.

The 95% confidence level expected and observed upper limits on the product of $g^{2}_{tS}$ and $\bf{\it{B}}(\phi \rightarrow $$\mu\mu$$)$ of the $t\bar{t} \phi$ signal with scalar couplings, where $g_{tS}$ denotes the coupling of the $\phi$ boson to the top quark and $\bf{\it{B}}(\phi \rightarrow $$\mu\mu$$)$ is the branching fraction of the $\phi$ boson into a muon pair. The vertical gray band indicates the mass region not considered in the analysis.

The 95% confidence level expected and observed upper limits on the product of $g^{2}_{tS}$ and $\bf{\it{B}}(\phi \rightarrow $$\tau\tau$$)$ of the $t\bar{t} \phi$ signal with scalar couplings, where $g_{tS}$ denotes the coupling of the $\phi$ boson to the top quark and $\bf{\it{B}}(\phi \rightarrow $$\tau\tau$$)$ is the branching fraction of the $\phi$ boson into a tau pair.

The 95% confidence level expected and observed upper limits on the product of $g^{2}_{tPS}$ and $\bf{\it{B}}(\phi \rightarrow $ee$)$ of the $t\bar{t} \phi$ signal with pseudoscalar couplings, where $g_{tPS}$ denotes the coupling of the $\phi$ boson to the top quark and $\bf{\it{B}}(\phi \rightarrow $ee$)$ is the branching fraction of the $\phi$ boson into an electron pair. The vertical gray band indicates the mass region not considered in the analysis.

The 95% confidence level expected and observed upper limits on the product of $g^{2}_{tPS}$ and $\bf{\it{B}}(\phi \rightarrow $$\mu\mu$$)$ of the $t\bar{t} \phi$ signal with pseudoscalar couplings, where $g_{tPS}$ denotes the coupling of the $\phi$ boson to the top quark and $\bf{\it{B}}(\phi \rightarrow $$\mu\mu$$)$ is the branching fraction of the $\phi$ boson into a muon pair. The vertical gray band indicates the mass region not considered in the analysis.

The 95% confidence level expected and observed upper limits on the product of $g^{2}_{tPS}$ and $\bf{\it{B}}(\phi \rightarrow $$\tau\tau$$)$ of the $t\bar{t} \phi$ signal with pseudoscalar couplings, where $g_{tPS}$ denotes the coupling of the $\phi$ boson to the top quark and $\bf{\it{B}}(\phi \rightarrow $$\tau\tau$$)$ is the branching fraction of the $\phi$ boson into a tau pair.

The 95% confidence level expected and observed upper limits on the product of $sin^2 \theta$ and $\bf{\it{B}}(\phi \rightarrow $ee$)$ of the $t\bar{t} \phi$ signal with H-like production, where $\theta$ denotes the mixing angle of the Higgs boson with the $\phi$ boson and $\bf{\it{B}}(\phi \rightarrow $ee$)$ is the branching fraction of the $\phi$ boson into an electron pair. The vertical gray band indicates the mass region not considered in the analysis.

The 95% confidence level expected and observed upper limits on the product of $sin^2 \theta$ and $\bf{\it{B}}(\phi \rightarrow $$\mu\mu$$)$ of the $t\bar{t} \phi$ signal with H-like production, where $\theta$ denotes the mixing angle of the Higgs boson with the $\phi$ boson and $\bf{\it{B}}(\phi \rightarrow $$\mu\mu$$)$ is the branching fraction of the $\phi$ boson into a muon pair. The vertical gray band indicates the mass region not considered in the analysis.

The 95% confidence level expected and observed upper limits on the product of $sin^2 \theta$ and $\bf{\it{B}}(\phi \rightarrow $$\tau\tau$$)$ of the $t\bar{t} \phi$ signal with H-like production, where $\theta$ denotes the mixing angle of the Higgs boson with the $\phi$ boson and $\bf{\it{B}}(\phi \rightarrow $$\tau\tau$$)$ is the branching fraction of the $\phi$ boson into a tau pair.

The 95% confidence level expected and observed upper limits on the product of $\Lambda^{-2}_{S}$ and $\bf{\it{B}}(\phi \rightarrow $ee$)$ of the $W\phi$ signal with scalar couplings, where $\Lambda_{S}$ denotes the mass scale of the effective interaction and $\bf{\it{B}}(\phi \rightarrow $ee$)$ is the branching fraction of the $\phi$ boson into an electron pair. The vertical gray band indicates the mass region not considered in the analysis.

The 95% confidence level expected and observed upper limits on the product of $\Lambda^{-2}_{S}$ and $\bf{\it{B}}(\phi \rightarrow $$\mu\mu$$)$ of the $W\phi$ signal with scalar couplings, where $\Lambda_{S}$ denotes the mass scale of the effective interaction and $\bf{\it{B}}(\phi \rightarrow $$\mu\mu$$)$ is the branching fraction of the $\phi$ boson into a muon pair. The vertical gray band indicates the mass region not considered in the analysis.

The 95% confidence level expected and observed upper limits on the product of $\Lambda^{-2}_{S}$ and $\bf{\it{B}}(\phi \rightarrow $$\tau\tau$$)$ of the $W\phi$ signal with scalar couplings, where $\Lambda_{S}$ denotes the mass scale of the effective interaction and $\bf{\it{B}}(\phi \rightarrow $$\tau\tau$$)$ is the branching fraction of the $\phi$ boson into a tau pair.

The 95% confidence level expected and observed upper limits on the product of $\Lambda^{-2}_{PS}$ and $\bf{\it{B}}(\phi \rightarrow $ee$)$ of the $W\phi$ signal with pseudoscalar couplings, where $\Lambda_{PS}$ denotes the mass scale of the effective interaction and $\bf{\it{B}}(\phi \rightarrow $ee$)$ is the branching fraction of the $\phi$ boson into an electron pair. The vertical gray band indicates the mass region not considered in the analysis.

The 95% confidence level expected and observed upper limits on the product of $\Lambda^{-2}_{PS}$ and $\bf{\it{B}}(\phi \rightarrow $$\mu\mu$$)$ of the $W\phi$ signal with pseudoscalar couplings, where $\Lambda_{PS}$ denotes the mass scale of the effective interaction and $\bf{\it{B}}(\phi \rightarrow $$\mu\mu$$)$ is the branching fraction of the $\phi$ boson into a muon pair. The vertical gray band indicates the mass region not considered in the analysis.

The 95% confidence level expected and observed upper limits on the product of $\Lambda^{-2}_{PS}$ and $\bf{\it{B}}(\phi \rightarrow $$\tau\tau$$)$ of the $W\phi$ signal with pseudoscalar couplings, where $\Lambda_{PS}$ denotes the mass scale of the effective interaction and $\bf{\it{B}}(\phi \rightarrow $$\tau\tau$$)$ is the branching fraction of the $\phi$ boson into a tau pair.

The 95% confidence level expected and observed upper limits on the product of $sin^2 \theta$ and $\bf{\it{B}}(\phi \rightarrow $ee$)$ of the $W\phi$ signal with H-like production, where $\theta$ denotes the mixing angle of the Higgs boson with the $\phi$ boson and $\bf{\it{B}}(\phi \rightarrow $ee$)$ is the branching fraction of the $\phi$ boson into an electron pair. The vertical gray band indicates the mass region not considered in the analysis.

The 95% confidence level expected and observed upper limits on the product of $sin^2 \theta$ and $\bf{\it{B}}(\phi \rightarrow $$\mu\mu$$)$ of the $W\phi$ signal with H-like production, where $\theta$ denotes the mixing angle of the Higgs boson with the $\phi$ boson and $\bf{\it{B}}(\phi \rightarrow $$\mu\mu$$)$ is the branching fraction of the $\phi$ boson into a muon pair. The vertical gray band indicates the mass region not considered in the analysis.

The 95% confidence level expected and observed upper limits on the product of $sin^2 \theta$ and $\bf{\it{B}}(\phi \rightarrow $$\tau\tau$$)$ of the $W\phi$ signal with H-like production, where $\theta$ denotes the mixing angle of the Higgs boson with the $\phi$ boson and $\bf{\it{B}}(\phi \rightarrow $$\tau\tau$$)$ is the branching fraction of the $\phi$ boson into a tau pair.

The 95% confidence level expected and observed upper limits on the product of $\Lambda^{-2}_{S}$ and $\bf{\it{B}}(\phi \rightarrow $ee$)$ of the $Z\phi$ signal with scalar couplings, where $\Lambda_{S}$ denotes the mass scale of the effective interaction and $\bf{\it{B}}(\phi \rightarrow $ee$)$ is the branching fraction of the $\phi$ boson into an electron pair. The vertical gray band indicates the mass region not considered in the analysis.

The 95% confidence level expected and observed upper limits on the product of $\Lambda^{-2}_{S}$ and $\bf{\it{B}}(\phi \rightarrow $$\mu\mu$$)$ of the $Z\phi$ signal with scalar couplings, where $\Lambda_{S}$ denotes the mass scale of the effective interaction and $\bf{\it{B}}(\phi \rightarrow $$\mu\mu$$)$ is the branching fraction of the $\phi$ boson into a muon pair. The vertical gray band indicates the mass region not considered in the analysis.

The 95% confidence level expected and observed upper limits on the product of $\Lambda^{-2}_{S}$ and $\bf{\it{B}}(\phi \rightarrow $$\tau\tau$$)$ of the $Z\phi$ signal with scalar couplings, where $\Lambda_{S}$ denotes the mass scale of the effective interaction and $\bf{\it{B}}(\phi \rightarrow $$\tau\tau$$)$ is the branching fraction of the $\phi$ boson into a tau pair.

The 95% confidence level expected and observed upper limits on the product of $\Lambda^{-2}_{PS}$ and $\bf{\it{B}}(\phi \rightarrow $ee$)$ of the $Z\phi$ signal with pseudoscalar couplings, where $\Lambda_{PS}$ denotes the mass scale of the effective interaction and $\bf{\it{B}}(\phi \rightarrow $ee$)$ is the branching fraction of the $\phi$ boson into an electron pair. The vertical gray band indicates the mass region not considered in the analysis.

The 95% confidence level expected and observed upper limits on the product of $\Lambda^{-2}_{PS}$ and $\bf{\it{B}}(\phi \rightarrow $$\mu\mu$$)$ of the $Z\phi$ signal with pseudoscalar couplings, where $\Lambda_{PS}$ denotes the mass scale of the effective interaction and $\bf{\it{B}}(\phi \rightarrow $$\mu\mu$$)$ is the branching fraction of the $\phi$ boson into a muon pair. The vertical gray band indicates the mass region not considered in the analysis.

The 95% confidence level expected and observed upper limits on the product of $\Lambda^{-2}_{PS}$ and $\bf{\it{B}}(\phi \rightarrow $$\tau\tau$$)$ of the $Z\phi$ signal with pseudoscalar couplings, where $\Lambda_{PS}$ denotes the mass scale of the effective interaction and $\bf{\it{B}}(\phi \rightarrow $$\tau\tau$$)$ is the branching fraction of the $\phi$ boson into a tau pair.

The 95% confidence level expected and observed upper limits on the product of $sin^2 \theta$ and $\bf{\it{B}}(\phi \rightarrow $ee$)$ of the $Z\phi$ signal with H-like production, where $\theta$ denotes the mixing angle of the Higgs boson with the $\phi$ boson and $\bf{\it{B}}(\phi \rightarrow $ee$)$ is the branching fraction of the $\phi$ boson into an electron pair. The vertical gray band indicates the mass region not considered in the analysis.

The 95% confidence level expected and observed upper limits on the product of $sin^2 \theta$ and $\bf{\it{B}}(\phi \rightarrow $$\mu\mu$$)$ of the $Z\phi$ signal with H-like production, where $\theta$ denotes the mixing angle of the Higgs boson with the $\phi$ boson and $\bf{\it{B}}(\phi \rightarrow $$\mu\mu$$)$ is the branching fraction of the $\phi$ boson into a muon pair. The vertical gray band indicates the mass region not considered in the analysis.

The 95% confidence level expected and observed upper limits on the product of $sin^2 \theta$ and $\bf{\it{B}}(\phi \rightarrow $$\tau\tau$$)$ of the $Z\phi$ signal with H-like production, where $\theta$ denotes the mixing angle of the Higgs boson with the $\phi$ boson and $\bf{\it{B}}(\phi \rightarrow $$\tau\tau$$)$ is the branching fraction of the $\phi$ boson into a tau pair.

The 95% confidence level observed upper limits on the product of $\sigma$($t \bar{t} \phi$) and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ for the $t \bar{t} \phi$ signal with scalar couplings, where $\sigma$ denotes the production cross section and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ is the branching fraction of the $\phi$ boson into a lepton pair of given flavor. Exclusions on the dielectron, dimuon, and ditau decay scenarios of the $\phi$ boson are shown with the green, blue, and orange solid lines, respectively. The red dash-dotted line is the theoretical prediction for $\sigma\bf{\it{B}}$ of the $t \bar{t} \phi$ signal. The vertical gray band indicates the mass region not considered in the analysis in the dielectron and dimuon decay scenarios of the $\phi$ boson.

The 95% confidence level observed upper limits on the product of $\sigma$($t \bar{t} \phi$) and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ for the $t \bar{t} \phi$ signal with pseudoscalar couplings, where $\sigma$ denotes the production cross section and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ is the branching fraction of the $\phi$ boson into a lepton pair of given flavor. Exclusions on the dielectron, dimuon, and ditau decay scenarios of the $\phi$ boson are shown with the green, blue, and orange solid lines, respectively. The red dash-dotted line is the theoretical prediction for $\sigma\bf{\it{B}}$ of the $t \bar{t} \phi$ signal. The vertical gray band indicates the mass region not considered in the analysis in the dielectron and dimuon decay scenarios of the $\phi$ boson.

The 95% confidence level observed upper limits on the product of $\sigma$($W\phi$) and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ for the $W\phi$ signal with scalar couplings, where $\sigma$ denotes the production cross section and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ is the branching fraction of the $\phi$ boson into a lepton pair of given flavor. Exclusions on the dielectron, dimuon, and ditau decay scenarios of the $\phi$ boson are shown with the green, blue, and orange solid lines, respectively. The red dash-dotted line is the theoretical prediction for $\sigma\bf{\it{B}}$ of the $W\phi$ signal. The vertical gray band indicates the mass region not considered in the analysis in the dielectron and dimuon decay scenarios of the $\phi$ boson.

The 95% confidence level observed upper limits on the product of $\sigma$($W\phi$) and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ for the $W\phi$ signal with pseudoscalar couplings, where $\sigma$ denotes the production cross section and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ is the branching fraction of the $\phi$ boson into a lepton pair of given flavor. Exclusions on the dielectron, dimuon, and ditau decay scenarios of the $\phi$ boson are shown with the green, blue, and orange solid lines, respectively. The red dash-dotted line is the theoretical prediction for $\sigma\bf{\it{B}}$ of the $W\phi$ signal. The vertical gray band indicates the mass region not considered in the analysis in the dielectron and dimuon decay scenarios of the $\phi$ boson.

The 95% confidence level observed upper limits on the product of $\sigma$($W\phi$) and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ for the $W\phi$ signal with H-like production, where $\sigma$ denotes the production cross section and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ is the branching fraction of the $\phi$ boson into a lepton pair of given flavor. Exclusions on the dielectron, dimuon, and ditau decay scenarios of the $\phi$ boson are shown with the green, blue, and orange solid lines, respectively. The red dash-dotted line is the theoretical prediction for $\sigma\bf{\it{B}}$ of the $W\phi$ signal. The vertical gray band indicates the mass region not considered in the analysis in the dielectron and dimuon decay scenarios of the $\phi$ boson.

The 95% confidence level observed upper limits on the product of $\sigma$($Z\phi$) and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ for the $Z\phi$ signal with scalar couplings, where $\sigma$ denotes the production cross section and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ is the branching fraction of the $\phi$ boson into a lepton pair of given flavor. Exclusions on the dielectron, dimuon, and ditau decay scenarios of the $\phi$ boson are shown with the green, blue, and orange solid lines, respectively. The red dash-dotted line is the theoretical prediction for $\sigma\bf{\it{B}}$ of the $Z\phi$ signal. The vertical gray band indicates the mass region not considered in the analysis in the dielectron and dimuon decay scenarios of the $\phi$ boson.

The 95% confidence level observed upper limits on the product of $\sigma$($Z\phi$) and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ for the $Z\phi$ signal with pseudoscalar couplings, where $\sigma$ denotes the production cross section and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ is the branching fraction of the $\phi$ boson into a lepton pair of given flavor. Exclusions on the dielectron, dimuon, and ditau decay scenarios of the $\phi$ boson are shown with the green, blue, and orange solid lines, respectively. The red dash-dotted line is the theoretical prediction for $\sigma\bf{\it{B}}$ of the $Z\phi$ signal. The vertical gray band indicates the mass region not considered in the analysis in the dielectron and dimuon decay scenarios of the $\phi$ boson.

The 95% confidence level observed upper limits on the product of $\sigma$($Z\phi$) and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ for the $Z\phi$ signal with H-like production, where $\sigma$ denotes the production cross section and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ is the branching fraction of the $\phi$ boson into a lepton pair of given flavor. Exclusions on the dielectron, dimuon, and ditau decay scenarios of the $\phi$ boson are shown with the green, blue, and orange solid lines, respectively. The red dash-dotted line is the theoretical prediction for $\sigma\bf{\it{B}}$ of the $Z\phi$ signal. The vertical gray band indicates the mass region not considered in the analysis in the dielectron and dimuon decay scenarios of the $\phi$ boson.

The 95% confidence level observed upper limits on the product of $g^{2}_{tS}$ and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ for the $t \bar{t} \phi$ signal with scalar couplings, where $g_{tS}$ denotes the coupling of the $\phi$ boson to the top quark and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ is the branching fraction of the $\phi$ boson into a lepton pair of given flavor. Exclusions on the dielectron, dimuon, and ditau decay scenarios of the $\phi$ boson are shown with the green, blue, and orange solid lines, respectively. The vertical gray band indicates the mass region not considered in the analysis in the dielectron and dimuon decay scenarios of the $\phi$ boson.

The 95% confidence level observed upper limits on the product of $g^{2}_{tPS}$ and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ for the $t \bar{t} \phi$ signal with pseudoscalar couplings, where $g_{tPS}$ denotes the coupling of the $\phi$ boson to the top quark and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ is the branching fraction of the $\phi$ boson into a lepton pair of given flavor. Exclusions on the dielectron, dimuon, and ditau decay scenarios of the $\phi$ boson are shown with the green, blue, and orange solid lines, respectively. The vertical gray band indicates the mass region not considered in the analysis in the dielectron and dimuon decay scenarios of the $\phi$ boson.

The 95% confidence level observed upper limits on the product of $sin^2 \theta$ and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ for the $t \bar{t} \phi$ signal with H-like production, where $\theta$ denotes the mixing angle of the Higgs boson with the $\phi$ boson and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ is the branching fraction of the $\phi$ boson into a lepton pair of given flavor. Exclusions on the dielectron, dimuon, and ditau decay scenarios of the $\phi$ boson are shown with the green, blue, and orange solid lines, respectively. The vertical gray band indicates the mass region not considered in the analysis in the dielectron and dimuon decay scenarios of the $\phi$ boson.

The 95% confidence level observed upper limits on the product of $\Lambda^{-2}_{S}$ and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ for the $W\phi$ signal with scalar couplings, where $\Lambda_{S}$ denotes the mass scale of the effective interaction and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ is the branching fraction of the $\phi$ boson into a lepton pair of given flavor. Exclusions on the dielectron, dimuon, and ditau decay scenarios of the $\phi$ boson are shown with the green, blue, and orange solid lines, respectively. The vertical gray band indicates the mass region not considered in the analysis in the dielectron and dimuon decay scenarios of the $\phi$ boson.

The 95% confidence level observed upper limits on the product of $\Lambda^{-2}_{PS}$ and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ for the $W\phi$ signal with pseudoscalar couplings, where $\Lambda_{PS}$ denotes the mass scale of the effective interaction and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ is the branching fraction of the $\phi$ boson into a lepton pair of given flavor. Exclusions on the dielectron, dimuon, and ditau decay scenarios of the $\phi$ boson are shown with the green, blue, and orange solid lines, respectively. The vertical gray band indicates the mass region not considered in the analysis in the dielectron and dimuon decay scenarios of the $\phi$ boson.

The 95% confidence level observed upper limits on the product of $sin^2 \theta$ and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ for the $W\phi$ signal with H-like production, where $\theta$ denotes the mixing angle of the Higgs boson with the $\phi$ boson and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ is the branching fraction of the $\phi$ boson into a lepton pair of given flavor. Exclusions on the dielectron, dimuon, and ditau decay scenarios of the $\phi$ boson are shown with the green, blue, and orange solid lines, respectively. The vertical gray band indicates the mass region not considered in the analysis in the dielectron and dimuon decay scenarios of the $\phi$ boson.

The 95% confidence level observed upper limits on the product of $\Lambda^{-2}_{S}$ and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ for the $Z\phi$ signal with scalar couplings, where $\Lambda_{S}$ denotes the mass scale of the effective interaction and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ is the branching fraction of the $\phi$ boson into a lepton pair of given flavor. Exclusions on the dielectron, dimuon, and ditau decay scenarios of the $\phi$ boson are shown with the green, blue, and orange solid lines, respectively. The vertical gray band indicates the mass region not considered in the analysis in the dielectron and dimuon decay scenarios of the $\phi$ boson.

The 95% confidence level observed upper limits on the product of $\Lambda^{-2}_{PS}$ and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ for the $Z\phi$ signal with pseudoscalar couplings, where $\Lambda_{PS}$ denotes the mass scale of the effective interaction and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ is the branching fraction of the $\phi$ boson into a lepton pair of given flavor. Exclusions on the dielectron, dimuon, and ditau decay scenarios of the $\phi$ boson are shown with the green, blue, and orange solid lines, respectively. The vertical gray band indicates the mass region not considered in the analysis in the dielectron and dimuon decay scenarios of the $\phi$ boson.

The 95% confidence level observed upper limits on the product of $sin^2 \theta$ and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ for the $Z\phi$ signal with H-like production, where $\theta$ denotes the mixing angle of the Higgs boson with the $\phi$ boson and $\bf{\it{B}}(\phi \rightarrow \ell \ell)$ is the branching fraction of the $\phi$ boson into a lepton pair of given flavor. Exclusions on the dielectron, dimuon, and ditau decay scenarios of the $\phi$ boson are shown with the green, blue, and orange solid lines, respectively. The vertical gray band indicates the mass region not considered in the analysis in the dielectron and dimuon decay scenarios of the $\phi$ boson.

The product of acceptance and efficiency, $A\varepsilon$, for a scalar $\phi$ boson in the $t\bar{t} \phi$ signal (with inclusive $t\bar{t}$ decay) in each signal region in the dielectron decay scenario. Each value is computed as the ratio of the number of simulated signal events passing all selection criteria to the total number of simulated signal events, and includes the data-to-simulation correction factors described in the paper.

The product of acceptance and efficiency, $A\varepsilon$, for a scalar $\phi$ boson in the $t\bar{t} \phi$ signal (with inclusive $t\bar{t}$ decay) in each signal region in the dimuon decay scenario. Each value is computed as the ratio of the number of simulated signal events passing all selection criteria to the total number of simulated signal events, and includes the data-to-simulation correction factors described in the paper.

The product of acceptance and efficiency, $A\varepsilon$, for a scalar $\phi$ boson in the $t\bar{t} \phi$ signal (with inclusive $t\bar{t}$ decay) in each signal region in the ditau decay scenario. Each value is computed as the ratio of the number of simulated signal events passing all selection criteria to the total number of simulated signal events, and includes the data-to-simulation correction factors described in the paper.

The product of acceptance and efficiency, $A\varepsilon$, for a pseudoscalar $\phi$ boson in the $t\bar{t} \phi$ signal (with inclusive $t\bar{t}$ decay) in each signal region in the dielectron decay scenario. Each value is computed as the ratio of the number of simulated signal events passing all selection criteria to the total number of simulated signal events, and includes the data-to-simulation correction factors described in the paper.

The product of acceptance and efficiency, $A\varepsilon$, for a pseudoscalar $\phi$ boson in the $t\bar{t} \phi$ signal (with inclusive $t\bar{t}$ decay) in each signal region in the dimuon decay scenario. Each value is computed as the ratio of the number of simulated signal events passing all selection criteria to the total number of simulated signal events, and includes the data-to-simulation correction factors described in the paper.

The product of acceptance and efficiency, $A\varepsilon$, for a pseudoscalar $\phi$ boson in the $t\bar{t} \phi$ signal (with inclusive $t\bar{t}$ decay) in each signal region in the ditau decay scenario. Each value is computed as the ratio of the number of simulated signal events passing all selection criteria to the total number of simulated signal events, and includes the data-to-simulation correction factors described in the paper.

The product of acceptance and efficiency, $A\varepsilon$, for a scalar $\phi$ boson in the $W\phi$ signal (with leptonic $W$ decay) in each signal region in the dielectron decay scenario. Each value is computed as the ratio of the number of simulated signal events passing all selection criteria to the total number of simulated signal events, and includes the data-to-simulation correction factors described in the paper.

The product of acceptance and efficiency, $A\varepsilon$, for a scalar $\phi$ boson in the $W\phi$ signal (with leptonic $W$ decay) in each signal region in the dimuon decay scenario. Each value is computed as the ratio of the number of simulated signal events passing all selection criteria to the total number of simulated signal events, and includes the data-to-simulation correction factors described in the paper.

The product of acceptance and efficiency, $A\varepsilon$, for a scalar $\phi$ boson in the $W\phi$ signal (with leptonic $W$ decay) in each signal region in the ditau decay scenario. Each value is computed as the ratio of the number of simulated signal events passing all selection criteria to the total number of simulated signal events, and includes the data-to-simulation correction factors described in the paper.

The product of acceptance and efficiency, $A\varepsilon$, for a pseudoscalar $\phi$ boson in the $W\phi$ signal (with leptonic $W$ decay) in each signal region in the dielectron decay scenario. Each value is computed as the ratio of the number of simulated signal events passing all selection criteria to the total number of simulated signal events, and includes the data-to-simulation correction factors described in the paper.

The product of acceptance and efficiency, $A\varepsilon$, for a pseudoscalar $\phi$ boson in the $W\phi$ signal (with leptonic $W$ decay) in each signal region in the dimuon decay scenario. Each value is computed as the ratio of the number of simulated signal events passing all selection criteria to the total number of simulated signal events, and includes the data-to-simulation correction factors described in the paper.

The product of acceptance and efficiency, $A\varepsilon$, for a pseudoscalar $\phi$ boson in the $W\phi$ signal (with leptonic $W$ decay) in each signal region in the ditau decay scenario. Each value is computed as the ratio of the number of simulated signal events passing all selection criteria to the total number of simulated signal events, and includes the data-to-simulation correction factors described in the paper.

The product of acceptance and efficiency, $A\varepsilon$, for an H-like $\phi$ boson in the $W\phi$ signal (with leptonic $W$ decay) in each signal region in the dielectron decay scenario. Each value is computed as the ratio of the number of simulated signal events passing all selection criteria to the total number of simulated signal events, and includes the data-to-simulation correction factors described in the paper.

The product of acceptance and efficiency, $A\varepsilon$, for an H-like $\phi$ boson in the $W\phi$ signal (with leptonic $W$ decay) in each signal region in the dimuon decay scenario. Each value is computed as the ratio of the number of simulated signal events passing all selection criteria to the total number of simulated signal events, and includes the data-to-simulation correction factors described in the paper.

The product of acceptance and efficiency, $A\varepsilon$, for an H-like $\phi$ boson in the $W\phi$ signal (with leptonic $W$ decay) in each signal region in the ditau decay scenario. Each value is computed as the ratio of the number of simulated signal events passing all selection criteria to the total number of simulated signal events, and includes the data-to-simulation correction factors described in the paper.

The product of acceptance and efficiency, $A\varepsilon$, for a scalar $\phi$ boson in the $Z\phi$ signal (with leptonic $Z$ decay) in each signal region in the dielectron decay scenario. Each value is computed as the ratio of the number of simulated signal events passing all selection criteria to the total number of simulated signal events, and includes the data-to-simulation correction factors described in the paper.

The product of acceptance and efficiency, $A\varepsilon$, for a scalar $\phi$ boson in the $Z\phi$ signal (with leptonic $Z$ decay) in each signal region in the dimuon decay scenario. Each value is computed as the ratio of the number of simulated signal events passing all selection criteria to the total number of simulated signal events, and includes the data-to-simulation correction factors described in the paper.

The product of acceptance and efficiency, $A\varepsilon$, for a scalar $\phi$ boson in the $Z\phi$ signal (with leptonic $Z$ decay) in each signal region in the ditau decay scenario. Each value is computed as the ratio of the number of simulated signal events passing all selection criteria to the total number of simulated signal events, and includes the data-to-simulation correction factors described in the paper.

The product of acceptance and efficiency, $A\varepsilon$, for a pseudoscalar $\phi$ boson in the $Z\phi$ signal (with leptonic $Z$ decay) in each signal region in the dielectron decay scenario. Each value is computed as the ratio of the number of simulated signal events passing all selection criteria to the total number of simulated signal events, and includes the data-to-simulation correction factors described in the paper.

The product of acceptance and efficiency, $A\varepsilon$, for a pseudoscalar $\phi$ boson in the $Z\phi$ signal (with leptonic $Z$ decay) in each signal region in the dimuon decay scenario. Each value is computed as the ratio of the number of simulated signal events passing all selection criteria to the total number of simulated signal events, and includes the data-to-simulation correction factors described in the paper.

The product of acceptance and efficiency, $A\varepsilon$, for a pseudoscalar $\phi$ boson in the $Z\phi$ signal (with leptonic $Z$ decay) in each signal region in the ditau decay scenario. Each value is computed as the ratio of the number of simulated signal events passing all selection criteria to the total number of simulated signal events, and includes the data-to-simulation correction factors described in the paper.

The product of acceptance and efficiency, $A\varepsilon$, for an H-like $\phi$ boson in the $Z\phi$ signal (with leptonic $Z$ decay) in each signal region in the dielectron decay scenario. Each value is computed as the ratio of the number of simulated signal events passing all selection criteria to the total number of simulated signal events, and includes the data-to-simulation correction factors described in the paper.

The product of acceptance and efficiency, $A\varepsilon$, for an H-like $\phi$ boson in the $Z\phi$ signal (with leptonic $Z$ decay) in each signal region in the dimuon decay scenario. Each value is computed as the ratio of the number of simulated signal events passing all selection criteria to the total number of simulated signal events, and includes the data-to-simulation correction factors described in the paper.

The product of acceptance and efficiency, $A\varepsilon$, for an H-like $\phi$ boson in the $Z\phi$ signal (with leptonic $Z$ decay) in each signal region in the ditau decay scenario. Each value is computed as the ratio of the number of simulated signal events passing all selection criteria to the total number of simulated signal events, and includes the data-to-simulation correction factors described in the paper.

Selected signal shapes of the $W\phi$(ee) signal for illustration purposes. All shape parametrizations for all coupling scenarios of the $X\phi$(ee) signal are provided in the SignalShapes_XPhiToEleEle.root file, and a README file with instructions is provided under Additional Resources.

Selected signal shapes of the $W\phi$$(\mu\mu)$ signal for illustration purposes. All shape parametrizations for all coupling scenarios of the $X\phi$$(\mu\mu)$ signal are provided in the SignalShapes_XPhiToMuMu.root file, and a README file with instructions is provided under Additional Resources.

Selected signal shapes of the $W\phi$$(\tau\tau)$ signal for illustration purposes. All shape parametrizations for all coupling scenarios of the $X\phi$$(\tau\tau)$ signal are provided in the SignalShapes_XPhiToTauTau.root file, and a README file with instructions is provided under Additional Resources.

Signal yields for the charge scenarios considered in the analysis, as well as their associateds uncertainties.

Distribution of $N_{\text{hits}}^{\text{low dE/dx}}$ in the SR and the CR for the early 2016 data set, as well as for an FCP signal at a mass of 100 GeV and different charge scenarios. The vertical bars and the shaded area correspond to the statistical uncertainty in the SR and the CR, respectively. The p-value of the fit is 6%. The two lower panels show the ratio of the number of tracks observed in the CR (upper) and SR (lower), and the fit function. The vertical bars correspond to the uncertainty from statistical sources, while the shaded area shows the systematic uncertainty in the fit due to the choice of the fitting function and the binomial fit range as explained in low dE/dx the main text. Comparing with respect to the binomial fit starting at $N_{\text{hits}}^{\text{low dE/dx}} = 2$, and not $N_{\text{hits}}^{\text{low dE/dx}} = 1$, is needed to account for the fact that early 2016 data is more strongly affected low dE/dx by instrumental effects that widen the N hits distribution.

Distribution of $N_{\text{hits}}^{\text{low dE/dx}}$ in the SR and the CR for the late 2016 data set, as well as for an FCP signal at a mass of 100 GeV and different charge scenarios. The vertical bars and the shaded area correspond to the statistical uncertainty in the SR and the CR, respectively. The p-value of the fit is 78%. The two lower panels show the ratio of the number of tracks observed in the CR (upper) and SR (lower), and the fit function. The vertical bars correspond to the uncertainty from statistical sources, while the shaded area shows the systematic uncertainty in the fit due to the choice of the fitting function and the binomial fit range as explained in low dE/dx the main text.

Distribution of $N_{\text{hits}}^{\text{low dE/dx}}$ in the SR and the CR for the 2017 data set, as well as for an FCP signal at a mass of 100 GeV and different charge scenarios. The vertical bars and the shaded area correspond to the statistical uncertainty in the SR and the CR, respectively. The p-value of the fit is 65%. The two lower panels show the ratio of the number of tracks observed in the CR (upper) and SR (lower), and the fit function. The vertical bars correspond to the uncertainty from statistical sources, while the shaded area shows the systematic uncertainty in the fit due to the choice of the fitting function and the binomial fit range as explained in low dE/dx the main text.

Distribution of $N_{\text{hits}}^{\text{low dE/dx}}$ in the SR and the CR for the 2018 data set, as well as for an FCP signal at a mass of 100 GeV and different charge scenarios. The vertical bars and the shaded area correspond to the statistical uncertainty in the SR and the CR, respectively. The p-value of the fit is 9%. The two lower panels show the ratio of the number of tracks observed in the CR (upper) and SR (lower), and the fit function. The vertical bars correspond to the uncertainty from statistical sources, while the shaded area shows the systematic uncertainty in the fit due to the choice of the fitting function and the binomial fit range as explained in low dE/dx the main text.

Exclusion region (hatched) at 95% CL in the FCP charge-mass plane for the considered signal. The expected exclusion is shown with the associated 1 and 2 standard deviations $\sigma$ bands. Signal points at charges 0.9, 0.8, 2/3, 0.5, and 1/3 e are connected by straight lines to guide the eye. This is a conservative interpolation. Previous exclusions from CMS [Phys. Rev. D 87 (2013) 092008), JHEP 07 (2013) 122] as well as OPAL [Phys. Lett. B 572 (2003) 8] are given for comparison.

Observed 95% CL exclusion limits on the simplified models of chargino-pair production decaying via W bosons.

$+1\sigma$ observed 95% CL exclusion limits on the simplified models of chargino-pair production decaying via W bosons.

$-1\sigma$ observed 95% CL exclusion limits on the simplified models of chargino-pair production decaying via W bosons.

Expected 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and Z bosons.

$+1\sigma$ expected 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and Z bosons.

$-1\sigma$ expected 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and Z bosons.

Observed 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and Z bosons.

$+1\sigma$ observed 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and Z bosons.

$-1\sigma$ observed 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and Z bosons.

Expected 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and h bosons.

$+1\sigma$ expected 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and h bosons.

$-1\sigma$ expected 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and h bosons.

Observed 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and h bosons.

$+1\sigma$ observed 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and h bosons.

$-1\sigma$ observed 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and h bosons.

Expected 95% CL exclusion limits on the simplified models of higgsino GGM scenarios.

$+1\sigma$ expected 95% CL exclusion limits on the simplified models of higgsino GGM scenarios.

$-1\sigma$ expected 95% CL exclusion limits on the simplified models of higgsino GGM scenarios.

Observed 95% CL exclusion limits on the simplified models of higgsino GGM scenarios.

$+1\sigma$ observed 95% CL exclusion limits on the simplified models of higgsino GGM scenarios.

$-1\sigma$ observed 95% CL exclusion limits on the simplified models of higgsino GGM scenarios.

Observed upper limit on the signal cross section in fb for the production of $\tilde{\chi}_1^{+}\tilde{\chi}_{1}^{-}$.

The analyses used in combination for each scenario to set limits in models of the production of $\tilde{\chi}_1^{+}\tilde{\chi}_{1}^{-}$.

Observed upper limit on the signal cross section in fb for chargino--neutralino production decaying via W and Z bosons.

The analyses used in combination for each scenario to set limits in models of chargino--neutralino production decaying via W and Z bosons.

Expected 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and Z bosons.

$+1\sigma$ expected 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and Z bosons.

$-1\sigma$ expected 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and Z bosons.

Observed 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and Z bosons.

$+1\sigma$ observed 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and Z bosons.

$-1\sigma$ observed 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and Z bosons.

Observed upper limit on the signal cross section in fb for chargino--neutralino production decaying via W and h bosons.

The analyses used in combination for each scenario to set limits in models of chargino--neutralino production decaying via W and h bosons.

Observed upper limit on the signal cross section in fb for higgsino GGM scenarios.

The analyses used in combination for each scenario to set limits in higgsino GGM scenarios.

Absolute differential ttbar production cross section measured as function of ttbar rapidity in bins of ttbar mass at the parton level in the full phase space.