$R_\text{CP}$ plotted as a function of approximated $x_p$ for $-1.0 < y_b < 0.0$ and $0.0 < y^* < 1.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_p$ for $-1.0 < y_b < 0.0$ and $1.0 < y^* < 2.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_p$ for $-1.0 < y_b < 0.0$ and $2.0 < y^* < 3.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_p$ for $0.0 < y_b < 1.0$ and $0.0 < y^* < 1.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_p$ for $0.0 < y_b < 1.0$ and $1.0 < y^* < 2.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_p$ for $0.0 < y_b < 1.0$ and $2.0 < y^* < 4.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_p$ for $1.0 < y_b < 2.0$ and $0.0 < y^* < 1.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_p$ for $1.0 < y_b < 2.0$ and $1.0 < y^* < 2.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_p$ for $1.0 < y_b < 2.0$ and $2.0 < y^* < 3.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_p$ for $2.0 < y_b < 3.0$ and $0.0 < y^* < 1.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_p$ for $2.0 < y_b < 3.0$ and $1.0 < y^* < 2.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_p$ for $3.0 < y_b < 4.0$ and $0.0 < y^* < 1.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_{Pb}$ for $-3.0 < y_b < -2.0$ and $0.0 < y^* < 1.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_{Pb}$ for $-2.0 < y_b < -1.0$ and $0.0 < y^* < 1.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_{Pb}$ for $-2.0 < y_b < -1.0$ and $1.0 < y^* < 2.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_{Pb}$ for $-1.0 < y_b < 0.0$ and $0.0 < y^* < 1.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_{Pb}$ for $-1.0 < y_b < 0.0$ and $1.0 < y^* < 2.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_{Pb}$ for $-1.0 < y_b < 0.0$ and $2.0 < y^* < 3.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_{Pb}$ for $0.0 < y_b < 1.0$ and $0.0 < y^* < 1.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_{Pb}$ for $0.0 < y_b < 1.0$ and $1.0 < y^* < 2.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_{Pb}$ for $0.0 < y_b < 1.0$ and $2.0 < y^* < 4.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_{Pb}$ for $1.0 < y_b < 2.0$ and $0.0 < y^* < 1.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_{Pb}$ for $1.0 < y_b < 2.0$ and $1.0 < y^* < 2.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_{Pb}$ for $1.0 < y_b < 2.0$ and $2.0 < y^* < 3.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_{Pb}$ for $2.0 < y_b < 3.0$ and $0.0 < y^* < 1.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_{Pb}$ for $2.0 < y_b < 3.0$ and $1.0 < y^* < 2.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_{Pb}$ for $3.0 < y_b < 4.0$ and $0.0 < y^* < 1.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_\mathrm{F}$ for $-3.0 < y_b < -2.0$ and $0.0 < y^* < 1.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_\mathrm{F}$ for $-2.0 < y_b < -1.0$ and $0.0 < y^* < 1.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_\mathrm{F}$ for $-2.0 < y_b < -1.0$ and $1.0 < y^* < 2.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_\mathrm{F}$ for $-1.0 < y_b < 0.0$ and $0.0 < y^* < 1.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_\mathrm{F}$ for $-1.0 < y_b < 0.0$ and $1.0 < y^* < 2.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_\mathrm{F}$ for $-1.0 < y_b < 0.0$ and $2.0 < y^* < 3.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_\mathrm{F}$ for $0.0 < y_b < 1.0$ and $0.0 < y^* < 1.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_\mathrm{F}$ for $0.0 < y_b < 1.0$ and $1.0 < y^* < 2.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_\mathrm{F}$ for $0.0 < y_b < 1.0$ and $2.0 < y^* < 4.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_\mathrm{F}$ for $1.0 < y_b < 2.0$ and $0.0 < y^* < 1.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_\mathrm{F}$ for $1.0 < y_b < 2.0$ and $1.0 < y^* < 2.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_\mathrm{F}$ for $1.0 < y_b < 2.0$ and $2.0 < y^* < 3.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_\mathrm{F}$ for $2.0 < y_b < 3.0$ and $0.0 < y^* < 1.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_\mathrm{F}$ for $2.0 < y_b < 3.0$ and $1.0 < y^* < 2.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_\mathrm{F}$ for $3.0 < y_b < 4.0$ and $0.0 < y^* < 1.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$\langle T_{\text{AB}} \rangle$ normalized per-event dijet yields in $0-10$% collisions as a function of $\langle y_{\text{b}} \rangle$ for $40.0 < p_{\text{T,Avg}} \text{ [GeV]} < 49.6$ and $0.0 < y^{*} < 1.0$.

$\langle T_{\text{AB}} \rangle$ normalized per-event dijet yields in $60-90$% collisions as a function of $\langle y_{\text{b}} \rangle$ for $40.0 < p_{\text{T,Avg}} \text{ [GeV]} < 49.6$ and $0.0 < y^{*} < 1.0$.

$\langle T_{\text{AB}} \rangle$ normalized per-event dijet yields in $0-10$% collisions as a function of $\langle y_{\text{b}} \rangle$ for $49.6 < p_{\text{T,Avg}} \text{ [GeV]} < 61.4$ and $0.0 < y^{*} < 1.0$.

$\langle T_{\text{AB}} \rangle$ normalized per-event dijet yields in $60-90$% collisions as a function of $\langle y_{\text{b}} \rangle$ for $49.6 < p_{\text{T,Avg}} \text{ [GeV]} < 61.4$ and $0.0 < y^{*} < 1.0$.

$\langle T_{\text{AB}} \rangle$ normalized per-event dijet yields in $0-10$% collisions as a function of $\langle y_{\text{b}} \rangle$ for $61.4 < p_{\text{T,Avg}} \text{ [GeV]} < 76.1$ and $0.0 < y^{*} < 1.0$.

$\langle T_{\text{AB}} \rangle$ normalized per-event dijet yields in $60-90$% collisions as a function of $\langle y_{\text{b}} \rangle$ for $61.4 < p_{\text{T,Avg}} \text{ [GeV]} < 76.1$ and $0.0 < y^{*} < 1.0$.

$\langle T_{\text{AB}} \rangle$ normalized per-event dijet yields in $0-10$% collisions as a function of $\langle y_{\text{b}} \rangle$ for $40.0 < p_{\text{T,Avg}} \text{ [GeV]} < 49.6$ and $1.0 < y^{*} < 2.0$.

$\langle T_{\text{AB}} \rangle$ normalized per-event dijet yields in $60-90$% collisions as a function of $\langle y_{\text{b}} \rangle$ for $40.0 < p_{\text{T,Avg}} \text{ [GeV]} < 49.6$ and $1.0 < y^{*} < 2.0$.

$\langle T_{\text{AB}} \rangle$ normalized per-event dijet yields in $0-10$% collisions as a function of $\langle y_{\text{b}} \rangle$ for $49.6 < p_{\text{T,Avg}} \text{ [GeV]} < 61.4$ and $1.0 < y^{*} < 2.0$.

$\langle T_{\text{AB}} \rangle$ normalized per-event dijet yields in $60-90$% collisions as a function of $\langle y_{\text{b}} \rangle$ for $49.6 < p_{\text{T,Avg}} \text{ [GeV]} < 61.4$ and $1.0 < y^{*} < 2.0$.

$\langle T_{\text{AB}} \rangle$ normalized per-event dijet yields in $0-10$% collisions as a function of $\langle y_{\text{b}} \rangle$ for $61.4 < p_{\text{T,Avg}} \text{ [GeV]} < 76.1$ and $1.0 < y^{*} < 2.0$.

$\langle T_{\text{AB}} \rangle$ normalized per-event dijet yields in $60-90$% collisions as a function of $\langle y_{\text{b}} \rangle$ for $61.4 < p_{\text{T,Avg}} \text{ [GeV]} < 76.1$ and $1.0 < y^{*} < 2.0$.

$\langle T_{\text{AB}} \rangle$ normalized per-event dijet yields in $0-10$% collisions as a function of $\langle y_{\text{b}} \rangle$ for $40.0 < p_{\text{T,Avg}} \text{ [GeV]} < 49.6$ and $2.0 < y^{*} < 4.0$.

$\langle T_{\text{AB}} \rangle$ normalized per-event dijet yields in $60-90$% collisions as a function of $\langle y_{\text{b}} \rangle$ for $40.0 < p_{\text{T,Avg}} \text{ [GeV]} < 49.6$ and $2.0 < y^{*} < 4.0$.

$\langle T_{\text{AB}} \rangle$ normalized per-event dijet yields in $0-10$% collisions as a function of $\langle y_{\text{b}} \rangle$ for $49.6 < p_{\text{T,Avg}} \text{ [GeV]} < 61.4$ and $2.0 < y^{*} < 4.0$.

$\langle T_{\text{AB}} \rangle$ normalized per-event dijet yields in $60-90$% collisions as a function of $\langle y_{\text{b}} \rangle$ for $49.6 < p_{\text{T,Avg}} \text{ [GeV]} < 61.4$ and $2.0 < y^{*} < 4.0$.

$\langle T_{\text{AB}} \rangle$ normalized per-event dijet yields in $0-10$% collisions as a function of $\langle y_{\text{b}} \rangle$ for $61.4 < p_{\text{T,Avg}} \text{ [GeV]} < 76.1$ and $2.0 < y^{*} < 4.0$.

$\langle T_{\text{AB}} \rangle$ normalized per-event dijet yields in $60-90$% collisions as a function of $\langle y_{\text{b}} \rangle$ for $61.4 < p_{\text{T,Avg}} \text{ [GeV]} < 76.1$ and $2.0 < y^{*} < 4.0$.

The average tetrajet invariant mass distributions in data, along with the fitted background estimates for 0.16 < $\alpha$ < 0.18.

The average tetrajet invariant mass distributions in data, along with the fitted background estimates for 0.18 < $\alpha$ < 0.20.

The average tetrajet invariant mass distributions in data, along with the fitted background estimates for 0.20 < $\alpha$ < 0.22.

The average tetrajet invariant mass distributions in data, along with the fitted background estimates for 0.22 < $\alpha$ < 0.24.

The average tetrajet invariant mass distributions in data, along with the fitted background estimates for 0.24 < $\alpha$ < 0.26.

The average tetrajet invariant mass distributions in data, along with the fitted background estimates for 0.26 < $\alpha$ < 0.28.

The average tetrajet invariant mass distributions in data, along with the fitted background estimates for 0.28 < $\alpha$ < 0.30.

The average tetrajet invariant mass distributions in data, along with the fitted background estimates for 0.30 < $\alpha$ < 0.32.

The average tetrajet invariant mass distributions in data, along with the fitted background estimates for 0.32 < $\alpha$ < 0.34.

The average dijet invariant mass distributions in data, along with the fitted background estimates for 0.10 < $\alpha$ < 0.12.

The average dijet invariant mass distributions in data, along with the fitted background estimates for 0.12 < $\alpha$ < 0.14.

The average dijet invariant mass distributions in data, along with the fitted background estimates for 0.14 < $\alpha$ < 0.16.

The average dijet invariant mass distributions in data, along with the fitted background estimates for 0.16 < $\alpha$ < 0.18.

The average dijet invariant mass distributions in data, along with the fitted background estimates for 0.18 < $\alpha$ < 0.20.

The average dijet invariant mass distributions in data, along with the fitted background estimates for 0.20 < $\alpha$ < 0.22.

The average dijet invariant mass distributions in data, along with the fitted background estimates for 0.22 < $\alpha$ < 0.24.

The average dijet invariant mass distributions in data, along with the fitted background estimates for 0.24 < $\alpha$ < 0.26.

The average dijet invariant mass distributions in data, along with the fitted background estimates for 0.26 < $\alpha$ < 0.28.

The average dijet invariant mass distributions in data, along with the fitted background estimates for 0.28 < $\alpha$ < 0.30.

The average dijet invariant mass distributions in data, along with the fitted background estimates for 0.30 < $\alpha$ < 0.32.

The average dijet invariant mass distributions in data, along with the fitted background estimates for 0.32 < $\alpha$ < 0.34.

The expected and observed limits on $m_{4j}$ for signal templates using a 4-parameter fit function for 0.10 < $\alpha$ < 0.12.

The expected and observed limits on $m_{4j}$ for signal templates using a 4-parameter fit function for 0.12 < $\alpha$ < 0.14.

The expected and observed limits on $m_{4j}$ for signal templates using a 4-parameter fit function for 0.14 < $\alpha$ < 0.16.

The expected and observed limits on $m_{4j}$ for signal templates using a 4-parameter fit function for 0.16 < $\alpha$ < 0.18.

The expected and observed limits on $m_{4j}$ for signal templates using a 4-parameter fit function for 0.18 < $\alpha$ < 0.20.

The expected and observed limits on $m_{4j}$ for signal templates using a 4-parameter fit function for 0.20 < $\alpha$ < 0.22.

The expected and observed limits on $m_{4j}$ for signal templates using a 4-parameter fit function for 0.22 < $\alpha$ < 0.24.

The expected and observed limits on $m_{4j}$ for signal templates using a 4-parameter fit function for 0.24 < $\alpha$ < 0.26.

The expected and observed limits on $m_{4j}$ for signal templates using a 4-parameter fit function for 0.26 < $\alpha$ < 0.28.

The expected and observed limits on $m_{4j}$ for signal templates using a 4-parameter fit function for 0.28 < $\alpha$ < 0.30.

The expected and observed limits on $m_{4j}$ for signal templates using a 4-parameter fit function for 0.30 < $\alpha$ < 0.32.

The expected and observed limits on $m_{4j}$ for signal templates using a 4-parameter fit function for 0.32 < $\alpha$ < 0.34.

The expected and observed limits on $m_{\langle 2j \rangle}$ for signal templates using a 4-parameter fit function for 0.10 < $\alpha$ < 0.12.

The expected and observed limits on $m_{\langle 2j \rangle}$ for signal templates using a 4-parameter fit function for 0.12 < $\alpha$ < 0.14.

The expected and observed limits on $m_{\langle 2j \rangle}$ for signal templates using a 4-parameter fit function for 0.14 < $\alpha$ < 0.16.

The expected and observed limits on $m_{\langle 2j \rangle}$ for signal templates using a 4-parameter fit function for 0.16 < $\alpha$ < 0.18.

The expected and observed limits on $m_{\langle 2j \rangle}$ for signal templates using a 4-parameter fit function for 0.18 < $\alpha$ < 0.20.

The expected and observed limits on $m_{\langle 2j \rangle}$ for signal templates using a 4-parameter fit function for 0.20 < $\alpha$ < 0.22.

The expected and observed limits on $m_{\langle 2j \rangle}$ for signal templates using a 4-parameter fit function for 0.22 < $\alpha$ < 0.24.

The expected and observed limits on $m_{\langle 2j \rangle}$ for signal templates using a 4-parameter fit function for 0.24 < $\alpha$ < 0.26.

The expected and observed limits on $m_{\langle 2j \rangle}$ for signal templates using a 4-parameter fit function for 0.26 < $\alpha$ < 0.28.

The expected and observed limits on $m_{\langle 2j \rangle}$ for signal templates using a 4-parameter fit function for 0.28 < $\alpha$ < 0.30.

The expected and observed limits on $m_{\langle 2j \rangle}$ for signal templates using a 4-parameter fit function for 0.30 < $\alpha$ < 0.32.

The expected and observed limits on $m_{\langle 2j \rangle}$ for signal templates using a 4-parameter fit function for 0.32 < $\alpha$ < 0.34.

The expected and observed limits on $m_{4j}$ for Gaussian signal templates using a 4-parameter fit function for 0.10 < $\alpha$ < 0.12.

The expected and observed limits on $m_{4j}$ for Gaussian signal templates using a 4-parameter fit function for 0.12 < $\alpha$ < 0.14.

The expected and observed limits on $m_{4j}$ for Gaussian signal templates using a 4-parameter fit function for 0.14 < $\alpha$ < 0.16.

The expected and observed limits on $m_{4j}$ for Gaussian signal templates using a 4-parameter fit function for 0.16 < $\alpha$ < 0.18.

The expected and observed limits on $m_{4j}$ for Gaussian signal templates using a 4-parameter fit function for 0.18 < $\alpha$ < 0.20.

The expected and observed limits on $m_{4j}$ for Gaussian signal templates using a 4-parameter fit function for 0.20 < $\alpha$ < 0.22.

The expected and observed limits on $m_{4j}$ for Gaussian signal templates using a 4-parameter fit function for 0.22 < $\alpha$ < 0.24.

The expected and observed limits on $m_{4j}$ for Gaussian signal templates using a 4-parameter fit function for 0.24 < $\alpha$ < 0.26.

The expected and observed limits on $m_{4j}$ for Gaussian signal templates using a 4-parameter fit function for 0.26 < $\alpha$ < 0.28.

The expected and observed limits on $m_{4j}$ for Gaussian signal templates using a 4-parameter fit function for 0.28 < $\alpha$ < 0.30.

The expected and observed limits on $m_{4j}$ for Gaussian signal templates using a 4-parameter fit function for 0.30 < $\alpha$ < 0.32.

The expected and observed limits on $m_{4j}$ for Gaussian signal templates using a 4-parameter fit function for 0.32 < $\alpha$ < 0.34.

The expected and observed limits on $m_{\langle 2j \rangle}$ for Gaussian signal templates using a 4-parameter fit function for 0.10 < $\alpha$ < 0.12.

The expected and observed limits on $m_{\langle 2j \rangle}$ for Gaussian signal templates using a 4-parameter fit function for 0.12 < $\alpha$ < 0.14.

The expected and observed limits on $m_{\langle 2j \rangle}$ for Gaussian signal templates using a 4-parameter fit function for 0.14 < $\alpha$ < 0.16.

The expected and observed limits on $m_{\langle 2j \rangle}$ for Gaussian signal templates using a 4-parameter fit function for 0.16 < $\alpha$ < 0.18.

The expected and observed limits on $m_{\langle 2j \rangle}$ for Gaussian signal templates using a 4-parameter fit function for 0.18 < $\alpha$ < 0.20.

The expected and observed limits on $m_{\langle 2j \rangle}$ for Gaussian signal templates using a 4-parameter fit function for 0.20 < $\alpha$ < 0.22.

The expected and observed limits on $m_{\langle 2j \rangle}$ for Gaussian signal templates using a 4-parameter fit function for 0.22 < $\alpha$ < 0.24.

The expected and observed limits on $m_{\langle 2j \rangle}$ for Gaussian signal templates using a 4-parameter fit function for 0.24 < $\alpha$ < 0.26.

The expected and observed limits on $m_{\langle 2j \rangle}$ for Gaussian signal templates using a 4-parameter fit function for 0.26 < $\alpha$ < 0.28.

The expected and observed limits on $m_{\langle 2j \rangle}$ for Gaussian signal templates using a 4-parameter fit function for 0.28 < $\alpha$ < 0.30.

The expected and observed limits on $m_{\langle 2j \rangle}$ for Gaussian signal templates using a 4-parameter fit function for 0.30 < $\alpha$ < 0.32.

The expected and observed limits on $m_{\langle 2j \rangle}$ for Gaussian signal templates using a 4-parameter fit function for 0.32 < $\alpha$ < 0.34.

The product of the analysis acceptance and selection efficiency for all analysis selection criteria is shown as a function of $m_Y$ and $m_{X}/m_{Y}$.

The cross-section of the signal samples is shown as a function of $m_Y$ and $m_{X}/m_{Y}$.

Values of $\Delta Z$ for the discovery sensitivity, as defined in the text, as a function of the invariant mass $\textit{m}$. The j+b-jet invariant mass distribution is calculated in the 10 pb AR. Positive percentages indicate improvements in sensitivity. Horizontal dashed lines are drawn at 100% and 200% to guide the eye. The five benchmark BSM models are (1) charged Higgs boson production in association with a top quark, $tbH^{+}$ with $H^{+} \rightarrow t\bar{b}$; (2) a Kaluza-Klein gauge boson, $W_{KK}$, with the SM $W$ boson and a radion $\phi$; (3) a $Z'$ boson decaying to a composite lepton $E$ and $\ell$, with $E \rightarrow Z\ell$; (4) the sequential standard model $W' \rightarrow W Z' \rightarrow \ell\nu q\bar{q}$; (5) a simplified dark-matter model with an axial-vector mediator $Z' \rightarrow q\bar{q}$, where one of the quarks radiates a $W$ boson decaying to $\ell\nu$. The multiple markers shown for the composite-lepton model at the same invariant mass values correspond to different composite lepton ($E$) masses between 0.25 and 3.5 TeV. The center positions of the markers are set to the masses of the corresponding heavy particles.

Values of $\Delta Z$ for the discovery sensitivity, as defined in the text, as a function of the invariant mass $\textit{m}$. The 2b-jet invariant mass distribution is calculated in the 10 pb AR. Positive percentages indicate improvements in sensitivity. Horizontal dashed lines are drawn at 100% and 200% to guide the eye. The five benchmark BSM models are (1) charged Higgs boson production in association with a top quark, $tbH^{+}$ with $H^{+} \rightarrow t\bar{b}$; (2) a Kaluza-Klein gauge boson, $W_{KK}$, with the SM $W$ boson and a radion $\phi$; (3) a $Z'$ boson decaying to a composite lepton $E$ and $\ell$, with $E \rightarrow Z\ell$; (4) the sequential standard model $W' \rightarrow W Z' \rightarrow \ell\nu q\bar{q}$; (5) a simplified dark-matter model with an axial-vector mediator $Z' \rightarrow q\bar{q}$, where one of the quarks radiates a $W$ boson decaying to $\ell\nu$. The multiple markers shown for the composite-lepton model at the same invariant mass values correspond to different composite lepton ($E$) masses between 0.25 and 3.5 TeV. The center positions of the markers are set to the masses of the corresponding heavy particles.

Values of $\Delta Z$ for the discovery sensitivity, as defined in the text, as a function of the invariant mass $\textit{m}$. The j+e invariant mass distribution is calculated in the 10 pb AR. Positive percentages indicate improvements in sensitivity. Horizontal dashed lines are drawn at 100% and 200% to guide the eye. The five benchmark BSM models are (1) charged Higgs boson production in association with a top quark, $tbH^{+}$ with $H^{+} \rightarrow t\bar{b}$; (2) a Kaluza-Klein gauge boson, $W_{KK}$, with the SM $W$ boson and a radion $\phi$; (3) a $Z'$ boson decaying to a composite lepton $E$ and $\ell$, with $E \rightarrow Z\ell$; (4) the sequential standard model $W' \rightarrow W Z' \rightarrow \ell\nu q\bar{q}$; (5) a simplified dark-matter model with an axial-vector mediator $Z' \rightarrow q\bar{q}$, where one of the quarks radiates a $W$ boson decaying to $\ell\nu$. The multiple markers shown for the composite-lepton model at the same invariant mass values correspond to different composite lepton ($E$) masses between 0.25 and 3.5 TeV. The center positions of the markers are set to the masses of the corresponding heavy particles.

Values of $\Delta Z$ for the discovery sensitivity, as defined in the text, as a function of the invariant mass $\textit{m}$. The b-jet+e invariant mass distribution is calculated in the 10 pb AR. Positive percentages indicate improvements in sensitivity. Horizontal dashed lines are drawn at 100% and 200% to guide the eye. The five benchmark BSM models are (1) charged Higgs boson production in association with a top quark, $tbH^{+}$ with $H^{+} \rightarrow t\bar{b}$; (2) a Kaluza-Klein gauge boson, $W_{KK}$, with the SM $W$ boson and a radion $\phi$; (3) a $Z'$ boson decaying to a composite lepton $E$ and $\ell$, with $E \rightarrow Z\ell$; (4) the sequential standard model $W' \rightarrow W Z' \rightarrow \ell\nu q\bar{q}$; (5) a simplified dark-matter model with an axial-vector mediator $Z' \rightarrow q\bar{q}$, where one of the quarks radiates a $W$ boson decaying to $\ell\nu$. The multiple markers shown for the composite-lepton model at the same invariant mass values correspond to different composite lepton ($E$) masses between 0.25 and 3.5 TeV. The center positions of the markers are set to the masses of the corresponding heavy particles.

Values of $\Delta Z$ for the discovery sensitivity, as defined in the text, as a function of the invariant mass $\textit{m}$. The j+$\gamma$ invariant mass distribution is calculated in the 10 pb AR. Positive percentages indicate improvements in sensitivity. Horizontal dashed lines are drawn at 100% and 200% to guide the eye. The five benchmark BSM models are (1) charged Higgs boson production in association with a top quark, $tbH^{+}$ with $H^{+} \rightarrow t\bar{b}$; (2) a Kaluza-Klein gauge boson, $W_{KK}$, with the SM $W$ boson and a radion $\phi$; (3) a $Z'$ boson decaying to a composite lepton $E$ and $\ell$, with $E \rightarrow Z\ell$; (4) the sequential standard model $W' \rightarrow W Z' \rightarrow \ell\nu q\bar{q}$; (5) a simplified dark-matter model with an axial-vector mediator $Z' \rightarrow q\bar{q}$, where one of the quarks radiates a $W$ boson decaying to $\ell\nu$. The multiple markers shown for the composite-lepton model at the same invariant mass values correspond to different composite lepton ($E$) masses between 0.25 and 3.5 TeV. The center positions of the markers are set to the masses of the corresponding heavy particles.

Values of $\Delta Z$ for the discovery sensitivity, as defined in the text, as a function of the invariant mass $\textit{m}$. The j+$\mu$ invariant mass distribution is calculated in the 10 pb AR. Positive percentages indicate improvements in sensitivity. Horizontal dashed lines are drawn at 100% and 200% to guide the eye. The five benchmark BSM models are (1) charged Higgs boson production in association with a top quark, $tbH^{+}$ with $H^{+} \rightarrow t\bar{b}$; (2) a Kaluza-Klein gauge boson, $W_{KK}$, with the SM $W$ boson and a radion $\phi$; (3) a $Z'$ boson decaying to a composite lepton $E$ and $\ell$, with $E \rightarrow Z\ell$; (4) the sequential standard model $W' \rightarrow W Z' \rightarrow \ell\nu q\bar{q}$; (5) a simplified dark-matter model with an axial-vector mediator $Z' \rightarrow q\bar{q}$, where one of the quarks radiates a $W$ boson decaying to $\ell\nu$. The multiple markers shown for the composite-lepton model at the same invariant mass values correspond to different composite lepton ($E$) masses between 0.25 and 3.5 TeV. The center positions of the markers are set to the masses of the corresponding heavy particles.

Values of $\Delta Z$ for the discovery sensitivity, as defined in the text, as a function of the invariant mass $\textit{m}$. The b-jet+$\mu$ invariant mass distribution is calculated in the 10 pb AR. Positive percentages indicate improvements in sensitivity. Horizontal dashed lines are drawn at 100% and 200% to guide the eye. The five benchmark BSM models are (1) charged Higgs boson production in association with a top quark, $tbH^{+}$ with $H^{+} \rightarrow t\bar{b}$; (2) a Kaluza-Klein gauge boson, $W_{KK}$, with the SM $W$ boson and a radion $\phi$; (3) a $Z'$ boson decaying to a composite lepton $E$ and $\ell$, with $E \rightarrow Z\ell$; (4) the sequential standard model $W' \rightarrow W Z' \rightarrow \ell\nu q\bar{q}$; (5) a simplified dark-matter model with an axial-vector mediator $Z' \rightarrow q\bar{q}$, where one of the quarks radiates a $W$ boson decaying to $\ell\nu$. The multiple markers shown for the composite-lepton model at the same invariant mass values correspond to different composite lepton ($E$) masses between 0.25 and 3.5 TeV. The center positions of the markers are set to the masses of the corresponding heavy particles.

Values of $\Delta Z$ for the discovery sensitivity, as defined in the text, as a function of the invariant mass $\textit{m}$. The b-jet+$\gamma$ invariant mass distribution is calculated in the 10 pb AR. Positive percentages indicate improvements in sensitivity. Horizontal dashed lines are drawn at 100% and 200% to guide the eye. The five benchmark BSM models are (1) charged Higgs boson production in association with a top quark, $tbH^{+}$ with $H^{+} \rightarrow t\bar{b}$; (2) a Kaluza-Klein gauge boson, $W_{KK}$, with the SM $W$ boson and a radion $\phi$; (3) a $Z'$ boson decaying to a composite lepton $E$ and $\ell$, with $E \rightarrow Z\ell$; (4) the sequential standard model $W' \rightarrow W Z' \rightarrow \ell\nu q\bar{q}$; (5) a simplified dark-matter model with an axial-vector mediator $Z' \rightarrow q\bar{q}$, where one of the quarks radiates a $W$ boson decaying to $\ell\nu$. The multiple markers shown for the composite-lepton model at the same invariant mass values correspond to different composite lepton ($E$) masses between 0.25 and 3.5 TeV. The center positions of the markers are set to the masses of the corresponding heavy particles.

The 95% CL upper limits on the cross section times acceptance ($A$), efficiency ($\epsilon$), and branching ratio ($B$) for Gaussian-shaped signals with different signal widths. The limits are calculated for events with at least one lepton with pT > 60 GeV in the 10 pb AR. Two width hypotheses are shown; $\sigma X / mX = 0$ and $\sigma X / mX = 0.15$. In both cases, the detector resolution for jets is included in the simulation of signal samples. The $\pm1 \sigma$ and $\pm2 \sigma$ bands around the expected limit are shown for $\sigma X / mX = 0$ signals. Mass points are spaced 5% apart, relative to the preceding point, starting at 0.3 TeV.

Distributions of the anomaly score from the AE for data and five benchmark BSM models. Their legends, from top to bottom, are; (1) charged Higgs boson production in association with a top quark, $tbH^{+}$ with $H^{+} \rightarrow t\bar{b}$, with the $H^{+}$ mass of 2 TeV; (2) a 6 TeV Kaluza-Klein gauge boson, $W_{KK}$, with the SM $W$ boson and a radion $\phi$; (3) a 4 TeV $Z'$ boson decaying to a composite lepton $E$ with a mass of 0.5 TeV; (4) the sequential standard model $W' \rightarrow WZ' \rightarrow \ell\nu q\bar{q}$, with the $W'$ mass of 6.2 TeV and the $Z'$ mass of 6 TeV; (5) a simplified dark-matter model with an axial-vector mediator $Z' \rightarrow q\bar{q}$, where one of the quarks radiates a $W$ boson decaying to $\ell\nu$ with a mass of 6 TeV. The distributions for the BSM models are smoothed to remove fluctuations due to low MC event counts. The vertical lines indicate the start of the three anomaly regions (ARs). The labels of the three ARs indicate the visible cross section for hypothetical processes yielding the same number of events as observed in the 140 $fb^{-1}$ dataset. The AE is applied to preselected events without any requirements on invariant mass distributions.

Invariant mass distributions of $j+Y$ for $M_{jY}$ > 0.3 TeV after preselection along with the fit from Eq.(1). The fit is represented by red lines, and the associated uncertainties are indicated by yellow bands. The lower panels show the bin-by-bin significances of deviations from the fit, calculated as $(d_{\textit{i}} - f_{\textit{i}}) / \delta_{\textit{i}}$, where $d_{\textit{i}}$ is the data yield, $f_{\textit{i}}$ is the fit value, and $\delta_{i}$ is the uncertainty of data in the $\textit{i}$-th bin

Distributions of the anomaly score for data and several anomaly scenarios. The example BSM model (shown with the dashed blue lines) is the sequential standard model $W' \rightarrow WZ' \rightarrow \ell\nu q\bar{q}$. The mass of $W'$ is set to 2.2 TeV and the mass of the $Z'$ is set to 2 TeV. This model leads to the final state of one lepton, two jets, and small missing transverse energy that is similar to the SM backgrounds. The other histograms represent events from the same model with artificial modifications to represent anomalous events; (1) "Anomaly 1" is the case where all jets beyond the second jet ($N_{j}$ > 2) are replaced with photons; (2) "Anomaly 2" is the case where all jets beyond the second jet are replaced with $b$-jets; (3) "Anomaly 3" is the case of low-multiplicity events where all jets beyond the second jet are removed. The histograms are normalized to unit. The left peak near log(Loss) = -9 visible in Anomaly 1 and 2 is from the events without a third jet.

Summary of the observed and expected 95% CL upper limits on the cross section for $\mathrm{LQ}_{\mathrm{mix}}^{\mathrm{d}}$ pair production as a function of $m_{\mathrm{LQ}_{\mathrm{mix}}^{\mathrm{d}}}$ under the assumptions of B(LQ$\rightarrow t\mu$)=1.

Summary of observed and predicted yields in the four signal region categories. The background prediction is shown after the combined likelihood fit to data under the background-only hypothesis across all control region and signal region categories. The expected signal yields that are obtained by using their theoretical cross sections are also shown with their pre-fit uncertainties, assuming B=1 and $\mu$=1. The "Other" contribution is dominated by $t\bar{t}t\bar{t}$ and $t\bar{t}WW$ in the $3\ell$ SRs, whereas it is dominated by $tWZ$ and $t\bar{t}WW$ in the $4\ell$ SRs. Dashes refer to components that are negligible or not applicable.

Summary of the data, background and signal yields in the four signal region categories. The background prediction is shown before the combined likelihood fit to data. Dashes (--) refer to components that are negligible or not applicable.

Summary of the data and background yields in the seven control region categories. The background prediction is shown before the combined likelihood fit to data. Dashes (--) refer to components that are negligible or not applicable.

Summary of the data and background yields in the seven control region categories. The background prediction is shown after the combined likelihood fit to data under the background-only hypothesis across all control region categories. Dashes (--) refer to components that are negligible or not applicable.

Observed and expected upper limits at 95% CL on the production cross-section times branching fraction as a function of $m_{A'}$ at dark Higgs boson mass of 50 GeV

Observed and expected upper limits at 95% CL on the production cross-section times branching fraction as a function of $m_{A'}$ at dark Higgs boson mass of 60 GeV

Observed and expected upper limits at 95% CL on the production cross-section times branching fraction as a function of $m_{A'}$ at dark Higgs boson mass of 70 GeV

Observed 90% CL upper limits on $\alpha_{D}\epsilon^{2}$ as a function of $m_{A'}$ at dark Higgs boson mass of 20 GeV

Observed 90% CL upper limits on $\alpha_{D}\epsilon^{2}$ as a function of $m_{A'}$ at dark Higgs boson mass of 30 GeV

Observed 90% CL upper limits on $\alpha_{D}\epsilon^{2}$ as a function of $m_{A'}$ at dark Higgs boson mass of 40 GeV

Observed 90% CL upper limits on $\alpha_{D}\epsilon^{2}$ as a function of $m_{A'}$ at dark Higgs boson mass of 50 GeV

Observed 90% CL upper limits on $\alpha_{D}\epsilon^{2}$ as a function of $m_{A'}$ at dark Higgs boson mass of 60 GeV

Observed 90% CL upper limits on $\alpha_{D}\epsilon^{2}$ as a function of $m_{A'}$ at dark Higgs boson mass of 70 GeV

Observed 90% CL upper limits on $\epsilon^{2}$, assuming of $\alpha_{D}=0.1$, as a function of $m_{A'}$ at dark Higgs boson mass of 20 GeV

Observed 90% CL upper limits on $\epsilon^{2}$, assuming of $\alpha_{D}=0.1$, as a function of $m_{A'}$ at dark Higgs boson mass of 30 GeV

Observed 90% CL upper limits on $\epsilon^{2}$, assuming of $\alpha_{D}=0.1$, as a function of $m_{A'}$ at dark Higgs boson mass of 40 GeV

Observed 90% CL upper limits on $\epsilon^{2}$, assuming of $\alpha_{D}=0.1$, as a function of $m_{A'}$ at dark Higgs boson mass of 50 GeV

Observed 90% CL upper limits on $\epsilon^{2}$, assuming of $\alpha_{D}=0.1$, as a function of $m_{A'}$ at dark Higgs boson mass of 60 GeV

Observed 90% CL upper limits on $\epsilon^{2}$, assuming of $\alpha_{D}=0.1$, as a function of $m_{A'}$ at dark Higgs boson mass of 70 GeV

Observed and expected upper limits at 95% CL on the branching fraction as a function of $m_{A'}$ at dark Higgs boson mass of 20 GeV

Observed and expected upper limits at 95% CL on the branching fraction as a function of $m_{A'}$ at dark Higgs boson mass of 30 GeV

Observed and expected upper limits at 95% CL on the branching fraction as a function of $m_{A'}$ at dark Higgs boson mass of 40 GeV

Observed and expected upper limits at 95% CL on the branching fraction as a function of $m_{A'}$ at dark Higgs boson mass of 50 GeV

Observed and expected upper limits at 95% CL on the branching fraction as a function of $m_{A'}$ at dark Higgs boson mass of 60 GeV

Observed and expected upper limits at 95% CL on the branching fraction as a function of $m_{A'}$ at dark Higgs boson mass of 70 GeV

Observed and expected upper limits at 95% CL on $\alpha_{D}\epsilon^{2}$ as a function of $m_{A'}$ at dark Higgs boson mass of 20 GeV

Observed and expected upper limits at 95% CL on $\alpha_{D}\epsilon^{2}$ as a function of $m_{A'}$ at dark Higgs boson mass of 30 GeV

Observed and expected upper limits at 95% CL on $\alpha_{D}\epsilon^{2}$ as a function of $m_{A'}$ at dark Higgs boson mass of 40 GeV

Observed and expected upper limits at 95% CL on $\alpha_{D}\epsilon^{2}$ as a function of $m_{A'}$ at dark Higgs boson mass of 50 GeV

Observed and expected upper limits at 95% CL on $\alpha_{D}\epsilon^{2}$ as a function of $m_{A'}$ at dark Higgs boson mass of 60 GeV

Observed and expected upper limits at 95% CL on $\alpha_{D}\epsilon^{2}$ as a function of $m_{A'}$ at dark Higgs boson mass of 70 GeV

Events in bins of the $E_{miss}^T$ in the SR.

Di-muon mass distribution for the $\mu\mu\mu$ signal region for data and expected background. The expected signal distribution for $m_a = 35$ GeV is shown assuming $\sigma(t\bar{t}a)\times \text{Br}(a\rightarrow\mu\mu) = 4$ fb. Rare background processes include $ZZ+$jets, $WWZ$, $WZZ$, $ZZZ$, and $t\bar{t}t\bar{t}$.

Fit of the Double Crystal Ball width as a function of the $a$-boson mass in the $e\mu\mu$ channel.

Expected and observed 95% CL upper limit on signal cross section as a function of $m_a$ for $t\bar{t}a$.

Expected and observed 95% CL upper limit on signal cross section as a function of $m_a$ for $H^{+}\rightarrow aW$, considering a top pair cross section of $\sigma(pp\rightarrow t\bar{t})= 833$ pb for the charged Higgs boson mass, $m_{H^{+}} = 120$ GeV.

Expected and observed 95% CL upper limit on signal cross section as a function of $m_a$ for $H^{+}\rightarrow aW$, considering a top pair cross section of $\sigma(pp\rightarrow t\bar{t})= 833$ pb for the charged Higgs boson mass, $m_{H^{+}} = 140$ GeV.

Expected and observed 95% CL upper limit on signal cross section as a function of $m_a$ for $H^{+}\rightarrow aW$, considering a top pair cross section of $\sigma(pp\rightarrow t\bar{t})= 833$ pb for the charged Higgs boson mass, $m_{H^{+}} = 160$ GeV.

Comparison of the expected background with data in a region dominated by non-prompt background. The region is defined exactly like the $e\mu\mu$ signal region but requiring the two selected muons to have the same electrical charge.

Scan of the observed p-value as a function of $m_a$ for the background-only hypothesis.

Scan of the observed p-value as a function of $m_a$ for the background-only hypothesis for $e\mu\mu$ channel.

Scan of the observed p-value as a function of $m_a$ for the background-only hypothesis for $\mu\mu\mu$ channel.

Acceptance times efficiency for the $t\bar{t}a$, $a\rightarrow \mu\mu$ signal as a function of the $m_a$ hypothesis.

Acceptance times efficiency for the $t \rightarrow bH^+$, $H^+ \rightarrow W^+ a$, $a\rightarrow \mu\mu$ signal as a function of the $m_a$ and $m_{H^+}$ hypotheses, for the $e\mu\mu$ signal region. The upper left region of the plot corresponds to signals for which on-shell decays of $H^+ \rightarrow Wa$ are not possible. The CP conjugate process is also included.

Acceptance times efficiency for the $t \rightarrow bH^+ $, $H^+ \rightarrow W^+ a$, $a\rightarrow \mu\mu$ signal as a function of the $m_a$ and $m_{H^+}$ hypotheses, for the $\mu\mu\mu$ signal region. The upper left region of the plot corresponds to signals for which on-shell decays of $H^+ \rightarrow Wa$ are not possible. The CP conjugate process is also included.

Expected lower limits on $\tan\beta$ for the $t\rightarrow H^{+}b, H^{+}\rightarrow aW, a\rightarrow\mu\mu$ signal in the context of the 2HDM as a function of $m_{H^{+}}$ and $m_a$.

Observed lower limits on $\tan\beta$ for the $t\rightarrow H^{+}b, H^{+}\rightarrow aW, a\rightarrow\mu\mu$ signal in the context of the 2HDM as a function of $m_{H^{+}}$ and $m_a$.

Cutflow for two signal mass points for $t\bar{t}a$, $m_{a} = 20$ GeV and $m_{a} = 60$ GeV, and one signal mass point for $H^+ \rightarrow Wa$ for the electron channel $e\mu\mu$. For the signal yields, a cross section times branching ratio of 1 fb is assumed. The yields are presented before the profile likelihood fit.

Cutflow for the dominant backgrounds estimated from simulation ($t\bar{t}Z$, $WZ$, $t\bar{t}H$) and data, for the electron channel $e\mu\mu$. The yields are presented before the profile likelihood fit.

Cutflow for the signal mass point $t\bar{t}a$, $m_{a} = 20$ GeV, as well as the dominant backgrounds estimated from simulation ($t\bar{t}Z$, $WZ$, $t\bar{t}H$) and data, for the corresponding signal mass hypothesis, for the muon channel $\mu\mu\mu$. For the signal yields, a cross section times branching ratio of 1 fb is assumed. The yields are presented before the profile likelihood fit.

Cutflow for the signal mass point $t\bar{t}a$, $m_{a} = 60$ GeV, as well as the dominant backgrounds estimated from simulation ($t\bar{t}Z$, $WZ$, $t\bar{t}H$) and data, for the corresponding signal mass hypothesis, for the muon channel $\mu\mu\mu$. For the signal yields, a cross section times branching ratio of 1 fb is assumed. The yields are presented before the profile likelihood fit.

Cutflow for $H^+ \rightarrow W a$ with $m_{H^{+}} = 120$ GeV, $m_{a} = 30$ GeV for the muon channel $\mu\mu\mu$. A cross section times branching ratio of 1 fb is assumed. The yields are presented before the profile likelihood fit.

Total yields in the $e\mu\mu$ and $\mu\mu\mu$ signal regions for the expected background and data after the profile likelihood fit for a $m_a = 30$ GeV signal mass hypothesis.

Total efficiencies for the selection of signal events after categorization and application of the tighter photon $E_{\mathrm{T}}^{\gamma}$ selection used to optimize the signal significance spin-1 $q\bar{q'}\to X^{\pm} \to W^{\pm}\gamma$. In addition to the total efficiency, contributions to the signal selection from each of the separate event categories are shown. The efficiencies calculated from MC samples with $W/Z$ hadronic decays are shown as the points on each curve. The line presents interpolated results.

Total efficiencies for the selection of signal events after categorization and application of the tighter photon $E_{\mathrm{T}}^{\gamma}$ selection used to optimize the signal significance spin-2 $q\bar{q}\to X^0 \to Z\gamma$. In addition to the total efficiency, contributions to the signal selection from each of the separate event categories are shown. The efficiencies calculated from MC samples with $W/Z$ hadronic decays are shown as the points on each curve. The line presents interpolated results.

Total efficiencies for the selection of signal events after categorization and application of the tighter photon $E_{\mathrm{T}}^{\gamma}$ selection used to optimize the signal significance spin-2 $gg\to X^0 \to Z\gamma$. In addition to the total efficiency, contributions to the signal selection from each of the separate event categories are shown. The efficiencies calculated from MC samples with $W/Z$ hadronic decays are shown as the points on each curve. The line presents interpolated results.

The $m_{J\gamma}$ distributions of data events selected for the spin-1 $q\bar{q'}\to X^{\pm} \to W^{\pm}\gamma$ search in the D2 category. The background-only fit function shape is shown as the solid curve overlaid with a shaded band corresponding to statistical uncertainties in background parameters. Various signal shapes with cross-sections corresponding to expected limits obtained in this analysis are shown as dashed lines.

The $m_{J\gamma}$ distributions of data events selected for the spin-1 $q\bar{q'}\to X^{\pm} \to W^{\pm}\gamma$ search in the WMASS category. The background-only fit function shape is shown as the solid curve overlaid with a shaded band corresponding to statistical uncertainties in background parameters. Various signal shapes with cross-sections corresponding to expected limits obtained in this analysis are shown as dashed lines.

The $m_{J\gamma}$ distributions of data events selected for the spin-0 $gg \to X^{0} \to Z\gamma$ search in the BTAG category. The background-only fit function shape is shown as the solid curve overlaid with a shaded band corresponding to statistical uncertainties in background parameters. Various signal shapes with cross-sections corresponding to expected limits obtained in this analysis are shown as dashed lines.

The $m_{J\gamma}$ distributions of data events selected for the spin-0 $gg \to X^{0} \to Z\gamma$ search in the D2 category. The background-only fit function shape is shown as the solid curve overlaid with a shaded band corresponding to statistical uncertainties in background parameters. Various signal shapes with cross-sections corresponding to expected limits obtained in this analysis are shown as dashed lines.

The $m_{J\gamma}$ distributions of data events selected for the spin-0 $gg \to X^{0} \to Z\gamma$ search in the ZMASS category. The background-only fit function shape is shown as the solid curve overlaid with a shaded band corresponding to statistical uncertainties in background parameters. Various signal shapes with cross-sections corresponding to expected limits obtained in this analysis are shown as dashed lines.

The $m_{J\gamma}$ distributions of data events selected for the spin-2 $gg \to X^{0} \to Z\gamma$ search in the BTAG category. The background-only fit function shape is shown as the solid curve overlaid with a shaded band corresponding to statistical uncertainties in background parameters. Various signal shapes with cross-sections corresponding to expected limits obtained in this analysis are shown as dashed lines.

The $m_{J\gamma}$ distributions of data events selected for the spin-2 $gg \to X^{0} \to Z\gamma$ search in the D2 category. The background-only fit function shape is shown as the solid curve overlaid with a shaded band corresponding to statistical uncertainties in background parameters. Various signal shapes with cross-sections corresponding to expected limits obtained in this analysis are shown as dashed lines.

The $m_{J\gamma}$ distributions of data events selected for the spin-2 $gg \to X^{0} \to Z\gamma$ search in the ZMASS category. The background-only fit function shape is shown as the solid curve overlaid with a shaded band corresponding to statistical uncertainties in background parameters. Various signal shapes with cross-sections corresponding to expected limits obtained in this analysis are shown as dashed lines.

The $m_{J\gamma}$ distributions of data events selected for the spin-2 $q\bar{q} \to X^{0} \to Z\gamma$ search in the BTAG category. The background-only fit function shape is shown as the solid curve overlaid with a shaded band corresponding to statistical uncertainties in background parameters. Various signal shapes with cross-sections corresponding to expected limits obtained in this analysis are shown as dashed lines.

The $m_{J\gamma}$ distributions of data events selected for the spin-2 $q\bar{q} \to X^{0} \to Z\gamma$ search in the D2 category. The background-only fit function shape is shown as the solid curve overlaid with a shaded band corresponding to statistical uncertainties in background parameters. Various signal shapes with cross-sections corresponding to expected limits obtained in this analysis are shown as dashed lines.

The $m_{J\gamma}$ distributions of data events selected for the spin-2 $q\bar{q} \to X^{0} \to Z\gamma$ search in the ZMASS category. The background-only fit function shape is shown as the solid curve overlaid with a shaded band corresponding to statistical uncertainties in background parameters. Various signal shapes with cross-sections corresponding to expected limits obtained in this analysis are shown as dashed lines.

The 95% CL upper limits on $\sigma(pp\to X)\times B(X\to W/Z\gamma)$ as a function of $m_{X}$ for spin-0 $gg \to X^{0} \to Z\gamma$. The observed limits are shown as a solid black line and the expected ones are shown as a dashed line with the 1$\sigma$ (2$\sigma$) uncertainty band presented as the green (yellow) band.

The 95% CL upper limits on $\sigma(pp\to X)\times B(X\to W/Z\gamma)$ as a function of $m_{X}$ for spin-2 $gg \to X^{0} \to Z\gamma$. The observed limits are shown as a solid black line and the expected ones are shown as a dashed line with the 1$\sigma$ (2$\sigma$) uncertainty band presented as the green (yellow) band.

The 95% CL upper limits on $\sigma(pp\to X)\times B(X\to W/Z\gamma)$ as a function of $m_{X}$ for spin-2 $q\bar{q} \to X^{0} \to Z\gamma$. The observed limits are shown as a solid black line and the expected ones are shown as a dashed line with the 1$\sigma$ (2$\sigma$) uncertainty band presented as the green (yellow) band.

The 95% CL upper limits on $\sigma(pp\to X)\times B(X\to W/Z\gamma)$ as a function of $m_{X}$ for spin-1 $q\bar{q'}\to X^{\pm} \to W^{\pm}\gamma$. The observed limits are shown as a solid black line and the expected ones are shown as a dashed line with the 1$\sigma$ (2$\sigma$) uncertainty band presented as the green (yellow) band.

The jet mass distribution of large-$R$ jets originating from the hadronic decay of $W$ and $Z$ bosons produced from the decay of BSM bosons with mass $m_X = 2000$ GeV. The decays simulated are for the production models $q\bar{q'}\to X^{\pm} \to W^{\pm}\gamma$ with a spin-1 resonance $X^{\pm}$ and $gg\to X^0 \to Z\gamma$ with a spin-0 resonance $X^{0}$.

The photon $E_{T}$ selection criteria as a function of resonance mass for D2 categories. Selections for four different signal channels are shown together.

The photon $E_{T}$ selection criteria as a function of resonance mass for ZMASS or WMASS categories. Selections for four different signal channels are shown together.