UrQMD model calculations for net-proton cumulant ratios and proton factorial cumulant ratios in Au+Au collisions from $\sqrt{s_{NN}}$ = 7.7 - 200 GeV for 0-5$\%$ centrality. Same choices of centrality definition are used as used for experimental data.

Significance of deviations of central 0-5$\%$ data from various choices of baselines or references.

Cumulant ratios C2/C1 and C4/C2 of net-proton distributions in Au+Au collisions at $\sqrt{s_{NN}}$ = 19.6 GeV as a function of multiplicity (RefMult3X).

Cumulant ratios C2/C1 and C4/C2 of net-proton distributions in Au+Au collisions at $\sqrt{s_{NN}}$ = 19.6 GeV as a function of average multiplicity (RefMult3X) for 8 centrality bins from 0-10$\%$ to 70-80$\%$. Data with and without CBWC are given.

Cumulant ratios C2/C1 and C4/C2 of net-proton distributions in Au+Au collisions at $\sqrt{s_{NN}}$ = 19.6 GeV as a function of average multiplicity (RefMult3X) for 16 centrality bins from 0-5$\%$ to 75-80$\%$. Data with and without CBWC are given.

Reference multiplicity distributions in Au+Au collisions at $\sqrt{s_{NN}}$ = 11.5 GeV from BES-II. Three choices of multiplicity distributions (RefMult3 scaled by efficiency factor of $\epsilon$ = 0.83 or 83$\%$ to mimic RefMult3 of BES-I, RefMult3, and RefMult3X) are presented.

Cumulant ratios C2/C1 and C4/C2 of net-proton distributions in Au+Au collisions at $\sqrt{s_{NN}}$ = 11.5 GeV from BES-II as a function of centrality obtained with various centrality definitions.

Reference multiplicity distributions (RefMult3, RefMult3X, and RefMult3A) in Au+Au collisions at $\sqrt{s_{NN}}$ = 19.6 GeV from UrQMD model. The RefMult3 and RefMult3X distributions have been scaled by an efficiency factor of $\epsilon$ = 77.9$\%$ to mimic the distribution in experimenal data.

Cumulant ratios C2/C1 and C4/C2 of net-proton distributions in Au+Au collisions at $\sqrt{s_{NN}}$ = 19.6 GeV from UrQMD model as a function of centrality obtained with various centrality definitions (RefMult3, RefMult3X, and RefMult3A). The RefMult3 and RefMult3X distributions have been scaled by an efficiency factor of $\epsilon$ = 77.9$\%$ to mimic the distribution in experimenal data.

Collision energy dependence of net-proton C4/C2 in Au+Au collisions at $\sqrt{s_{NN}}$ = 7.7 - 27 GeV from BES-II obtained with RefMult3 centrality definition.

Difference between net-proton C4/C2 (0-5$\%$) data from various choices of baselines or references as a function of collision energy from $\sqrt{s_{NN}}$ = 7.7 - 200 GeV.

An example of the measured energy distribution in a single OHCal tower, showing the MIP distribution from a GEANT-4 simulation of cosmic-ray muons from EcoMug.

$\frac{dE_T}{d\eta}$ measurements in Au+Au collisions at $\sqrt{s_\mathrm{_{NN}}} = 200$ GeV over the pseudorapidity range $\left|\eta\right| < 1.1$.

Measurement of $\frac{dE_T}{d\eta}$ in 0-5% central Au+Au events as a function of $\eta$ over the range $\left|\eta\right| < 1.1$.

Measured $\frac{dE_T}{d\eta}$ normalized by the estimated number of participant pairs ($0.5$$N_{part}$), as a function of $N_{part}$, using the full calorimeter system.

Measured $\frac{dE_T}{d\eta}$ normalized by the estimated number of participant pairs ($0.5$$N_{part}$), as a function of $N_{part}$, predictions from AMPT.

Measured $\frac{dE_T}{d\eta}$ normalized by the estimated number of participant pairs ($0.5$$N_{part}$), as a function of $N_{part}$, predictions from EPOS.

Measured $\frac{dE_T}{d\eta}$ normalized by the estimated number of participant pairs ($0.5$$N_{part}$), as a function of $N_{part}$, predictions from HIJING.

$p_{T}$ dependence of $v_{2}$ for $\pi^{+}$ in Au+Au collisions at 3.9 GeV

$p_{T}$ dependence of $v_{2}$ for $\pi^{+}$ in Au+Au collisions at 4.5 GeV

$p_{T}$ dependence of $v_{2}$ for $\pi^{-}$ in Au+Au collisions at 3 GeV

$p_{T}$ dependence of $v_{2}$ for $\pi^{-}$ in Au+Au collisions at 3.2 GeV

$p_{T}$ dependence of $v_{2}$ for $\pi^{-}$ in Au+Au collisions at 3.5 GeV

$p_{T}$ dependence of $v_{2}$ for $\pi^{-}$ in Au+Au collisions at 3.9 GeV

$p_{T}$ dependence of $v_{2}$ for $\pi^{-}$ in Au+Au collisions at 4.5 GeV

$p_{T}$ dependence of $v_{2}$ for $K^{+}$ in Au+Au collisions at 3 GeV

$p_{T}$ dependence of $v_{2}$ for $K^{+}$ in Au+Au collisions at 3.2 GeV

$p_{T}$ dependence of $v_{2}$ for $K^{+}$ in Au+Au collisions at 3.5 GeV

$p_{T}$ dependence of $v_{2}$ for $K^{+}$ in Au+Au collisions at 3.9 GeV

$p_{T}$ dependence of $v_{2}$ for $K^{+}$ in Au+Au collisions at 4.5 GeV

$p_{T}$ dependence of $v_{2}$ for $K^{-}$ in Au+Au collisions at 3 GeV

$p_{T}$ dependence of $v_{2}$ for $K^{-}$ in Au+Au collisions at 3.2 GeV

$p_{T}$ dependence of $v_{2}$ for $K^{-}$ in Au+Au collisions at 3.5 GeV

$p_{T}$ dependence of $v_{2}$ for $K^{-}$ in Au+Au collisions at 3.9 GeV

$p_{T}$ dependence of $v_{2}$ for $K^{-}$ in Au+Au collisions at 4.5 GeV

$p_{T}$ dependence of $v_{2}$ for $K^{0}_{S}$ in Au+Au collisions at 3 GeV

$p_{T}$ dependence of $v_{2}$ for $K^{0}_{S}$ in Au+Au collisions at 3.2 GeV

$p_{T}$ dependence of $v_{2}$ for $K^{0}_{S}$ in Au+Au collisions at 3.5 GeV

$p_{T}$ dependence of $v_{2}$ for $K^{0}_{S}$ in Au+Au collisions at 3.9 GeV

$p_{T}$ dependence of $v_{2}$ for $K^{0}_{S}$ in Au+Au collisions at 4.5 GeV

$p_{T}$ dependence of $v_{2}$ for $p$ in Au+Au collisions at 3 GeV

$p_{T}$ dependence of $v_{2}$ for $p$ in Au+Au collisions at 3.2 GeV

$p_{T}$ dependence of $v_{2}$ for $p$ in Au+Au collisions at 3.5 GeV

$p_{T}$ dependence of $v_{2}$ for $p$ in Au+Au collisions at 3.9 GeV

$p_{T}$ dependence of $v_{2}$ for $p$ in Au+Au collisions at 4.5 GeV

$p_{T}$ dependence of $v_{2}$ for $\Lambda$ in Au+Au collisions at 3 GeV

$p_{T}$ dependence of $v_{2}$ for $\Lambda$ in Au+Au collisions at 3.2 GeV

$p_{T}$ dependence of $v_{2}$ for $\Lambda$ in Au+Au collisions at 3.5 GeV

$p_{T}$ dependence of $v_{2}$ for $\Lambda$ in Au+Au collisions at 3.9 GeV

$p_{T}$ dependence of $v_{2}$ for $\Lambda$ in Au+Au collisions at 4.5 GeV

The number of constituent quarks $n_q$ scaled $v_2$ as a function of $n_q$ scaled transverse kinetic energy for $\pi^{+}$ at 3 GeV

The number of constituent quarks $n_q$ scaled $v_2$ as a function of $n_q$ scaled transverse kinetic energy for $\pi^{+}$ at 3.2 GeV

The number of constituent quarks $n_q$ scaled $v_2$ as a function of $n_q$ scaled transverse kinetic energy for $\pi^{+}$ at 3.5 GeV

The number of constituent quarks $n_q$ scaled $v_2$ as a function of $n_q$ scaled transverse kinetic energy for $\pi^{+}$ at 3.9 GeV

The number of constituent quarks $n_q$ scaled $v_2$ as a function of $n_q$ scaled transverse kinetic energy for $\pi^{+}$ at 4.5 GeV

The number of constituent quarks $n_q$ scaled $v_2$ as a function of $n_q$ scaled transverse kinetic energy for $\pi^{-}$ at 3 GeV

The number of constituent quarks $n_q$ scaled $v_2$ as a function of $n_q$ scaled transverse kinetic energy for $\pi^{-}$ at 3.2 GeV

The number of constituent quarks $n_q$ scaled $v_2$ as a function of $n_q$ scaled transverse kinetic energy for $\pi^{-}$ at 3.5 GeV

The number of constituent quarks $n_q$ scaled $v_2$ as a function of $n_q$ scaled transverse kinetic energy for $\pi^{-}$ at 3.9 GeV

The number of constituent quarks $n_q$ scaled $v_2$ as a function of $n_q$ scaled transverse kinetic energy for $\pi^{-}$ at 4.5 GeV

The number of constituent quarks $n_q$ scaled $v_2$ as a function of $n_q$ scaled transverse kinetic energy for $K^{+}$ at 3 GeV

The number of constituent quarks $n_q$ scaled $v_2$ as a function of $n_q$ scaled transverse kinetic energy for $K^{+}$ at 3.2 GeV

The number of constituent quarks $n_q$ scaled $v_2$ as a function of $n_q$ scaled transverse kinetic energy for $K^{+}$ at 3.5 GeV

The number of constituent quarks $n_q$ scaled $v_2$ as a function of $n_q$ scaled transverse kinetic energy for $K^{+}$ at 3.9 GeV

The number of constituent quarks $n_q$ scaled $v_2$ as a function of $n_q$ scaled transverse kinetic energy for $K^{+}$ at 4.5 GeV

The number of constituent quarks $n_q$ scaled $v_2$ as a function of $n_q$ scaled transverse kinetic energy for $K^{-}$ at 3 GeV

The number of constituent quarks $n_q$ scaled $v_2$ as a function of $n_q$ scaled transverse kinetic energy for $K^{-}$ at 3.2 GeV

The number of constituent quarks $n_q$ scaled $v_2$ as a function of $n_q$ scaled transverse kinetic energy for $K^{-}$ at 3.5 GeV

The number of constituent quarks $n_q$ scaled $v_2$ as a function of $n_q$ scaled transverse kinetic energy for $K^{-}$ at 3.9 GeV

The number of constituent quarks $n_q$ scaled $v_2$ as a function of $n_q$ scaled transverse kinetic energy for $K^{-}$ at 4.5 GeV

The number of constituent quarks $n_q$ scaled $v_2$ as a function of $n_q$ scaled transverse kinetic energy for $K^{0}_{S}$ at 3 GeV

The number of constituent quarks $n_q$ scaled $v_2$ as a function of $n_q$ scaled transverse kinetic energy for $K^{0}_{S}$ at 3.2 GeV

The number of constituent quarks $n_q$ scaled $v_2$ as a function of $n_q$ scaled transverse kinetic energy for $K^{0}_{S}$ at 3.5 GeV

The number of constituent quarks $n_q$ scaled $v_2$ as a function of $n_q$ scaled transverse kinetic energy for $K^{0}_{S}$ at 3.9 GeV

The number of constituent quarks $n_q$ scaled $v_2$ as a function of $n_q$ scaled transverse kinetic energy for $K^{0}_{S}$ at 4.5 GeV

The number of constituent quarks $n_q$ scaled $v_2$ as a function of $n_q$ scaled transverse kinetic energy for $p$ at 3 GeV

The number of constituent quarks $n_q$ scaled $v_2$ as a function of $n_q$ scaled transverse kinetic energy for $p$ at 3.2 GeV

The number of constituent quarks $n_q$ scaled $v_2$ as a function of $n_q$ scaled transverse kinetic energy for $p$ at 3.5 GeV

The number of constituent quarks $n_q$ scaled $v_2$ as a function of $n_q$ scaled transverse kinetic energy for $p$ at 3.9 GeV

The number of constituent quarks $n_q$ scaled $v_2$ as a function of $n_q$ scaled transverse kinetic energy for $p$ at 4.5 GeV

The number of constituent quarks $n_q$ scaled $v_2$ as a function of $n_q$ scaled transverse kinetic energy for $\Lambda$ at 3 GeV

The number of constituent quarks $n_q$ scaled $v_2$ as a function of $n_q$ scaled transverse kinetic energy for $\Lambda$ at 3.2 GeV

The number of constituent quarks $n_q$ scaled $v_2$ as a function of $n_q$ scaled transverse kinetic energy for $\Lambda$ at 3.5 GeV

The number of constituent quarks $n_q$ scaled $v_2$ as a function of $n_q$ scaled transverse kinetic energy for $\Lambda$ at 3.9 GeV

The number of constituent quarks $n_q$ scaled $v_2$ as a function of $n_q$ scaled transverse kinetic energy for $\Lambda$ at 4.5 GeV

The energy dependence of $p_T$ integrated $v_2$ for $\pi^{\pm}$, $K^{\pm}$, $K^{0}_{S}$, $p$, and $\Lambda$ in 10-40\% centrality from Au+Au collisions at $\sqrt{s_{\text{NN}}}$ = 3.0, 3.2, 3.5, 3.9, and 4.5 GeV.

The energy dependence of $n_{q}$ scaled $v_{2}$ ratios of $v_{2}^{q}(\pi^{+}) / v_{2}^{q}(K^{+})$ and $v_{2}^{q}(p) / v_{2}^{q}(K^{+})$ at ($m_T - m_0$)/$n_q$ = 0.4 GeV/$c^2$

Signal-selection efficiency as a function of the di-tau invariant mass squared $q^2$ for simulated events in the SR. The error bars indicate the statistical uncertainty.

The 95% CL limits on the cross-section $\sigma(pp \rightarrow Z' \rightarrow \chi \chi$) times branching ratio B in fb with all statistical and systematic uncertainties, for the $R_{\text{inv}}=$0.6 signal points.

Data yield in the PFN signal region.

Yield of data in the ANTELOPE signal region in the binning used for BumpHunter fitting.

$M_{\tau}$ distribution in signal region, (OS$\mu$, Belle II)

$M_{\tau}$ distribution in signal region, (SS$e$, Belle)

$M_{\tau}$ distribution in signal region, (SS$e$, Belle II)

$M_{\tau}$ distribution in signal region, (SS$\mu$, Belle)

$M_{\tau}$ distribution in signal region, (SS$\mu$, Belle II)

Efficiency as function of the invariant mass squared $m^2(K^{*0}\ell)$ and $m^2(K^{*0}t_{\tau})$, where $t_{\tau}$ is the track from the $\tau$, (OS$e$, Belle)

Efficiency as function of the invariant mass squared $m^2(K^{*0}\ell)$ and $m^2(K^{*0}t_{\tau})$, where $t_{\tau}$ is the track from the $\tau$, (OS$e$, Belle II)

Efficiency as function of the invariant mass squared $m^2(K^{*0}\ell)$ and $m^2(K^{*0}t_{\tau})$, where $t_{\tau}$ is the track from the $\tau$, (OS$\mu$, Belle)

Efficiency as function of the invariant mass squared $m^2(K^{*0}\ell)$ and $m^2(K^{*0}t_{\tau})$, where $t_{\tau}$ is the track from the $\tau$, (OS$\mu$, Belle II)

Efficiency as function of the invariant mass squared $m^2(K^{*0}\ell)$ and $m^2(K^{*0}t_{\tau})$, where $t_{\tau}$ is the track from the $\tau$, (SS$e$, Belle)

Efficiency as function of the invariant mass squared $m^2(K^{*0}\ell)$ and $m^2(K^{*0}t_{\tau})$, where $t_{\tau}$ is the track from the $\tau$, (SS$e$, Belle II)

Efficiency as function of the invariant mass squared $m^2(K^{*0}\ell)$ and $m^2(K^{*0}t_{\tau})$, where $t_{\tau}$ is the track from the $\tau$, (SS$\mu$, Belle)

Efficiency as function of the invariant mass squared $m^2(K^{*0}\ell)$ and $m^2(K^{*0}t_{\tau})$, where $t_{\tau}$ is the track from the $\tau$, (SS$\mu$, Belle II)

Efficiency as function the helicity angle of the kaon $\cos\theta_{K}$, and the helicity angle of the lepton $\cos\theta_{\ell}$ in bin e the four-momentum-transfer $q^{2}$, (OS$e$, Belle)

Efficiency as function the helicity angle of the kaon $\cos\theta_{K}$, and the helicity angle of the lepton $\cos\theta_{\ell}$ in bin e the four-momentum-transfer $q^{2}$, (OS$e$, Belle II)

Efficiency as function the helicity angle of the kaon $\cos\theta_{K}$, and the helicity angle of the lepton $\cos\theta_{\ell}$ in bin e the four-momentum-transfer $q^{2}$, (OS$\mu$, Belle)

Efficiency as function the helicity angle of the kaon $\cos\theta_{K}$, and the helicity angle of the lepton $\cos\theta_{\ell}$ in bin e the four-momentum-transfer $q^{2}$, (OS$\mu$, Belle II)

Efficiency as function the helicity angle of the kaon $\cos\theta_{K}$, and the helicity angle of the lepton $\cos\theta_{\ell}$ in bin e the four-momentum-transfer $q^{2}$, (SS$e$, Belle)

Efficiency as function the helicity angle of the kaon $\cos\theta_{K}$, and the helicity angle of the lepton $\cos\theta_{\ell}$ in bin e the four-momentum-transfer $q^{2}$, (SS$e$, Belle II)

Efficiency as function the helicity angle of the kaon $\cos\theta_{K}$, and the helicity angle of the lepton $\cos\theta_{\ell}$ in bin e the four-momentum-transfer $q^{2}$, (SS$\mu$, Belle)

Efficiency as function the helicity angle of the kaon $\cos\theta_{K}$, and the helicity angle of the lepton $\cos\theta_{\ell}$ in bin e the four-momentum-transfer $q^{2}$, (SS$\mu$, Belle II)

Efficiency as function of the helicity angle of the kaon $\cos\theta_{K}$, (OS$e$, Belle)

Efficiency as function of the helicity angle of the kaon $\cos\theta_{K}$, (OS$e$, Belle II)

Efficiency as function of the helicity angle of the kaon $\cos\theta_{K}$, (OS$\mu$, Belle)

Efficiency as function of the helicity angle of the kaon $\cos\theta_{K}$, (OS$\mu$, Belle II)

Efficiency as function of the helicity angle of the kaon $\cos\theta_{K}$, (SS$e$, Belle)

Efficiency as function of the helicity angle of the kaon $\cos\theta_{K}$, (SS$e$, Belle II)

Efficiency as function of the helicity angle of the kaon $\cos\theta_{K}$, (SS$\mu$, Belle)

Efficiency as function of the helicity angle of the kaon $\cos\theta_{K}$, (SS$\mu$, Belle II)

Efficiency as function of the helicity angle of the lepton $\cos\theta_{\ell}$, (OS$e$, Belle)

Efficiency as function of the helicity angle of the lepton $\cos\theta_{\ell}$, (OS$e$, Belle II)

Efficiency as function of the helicity angle of the lepton $\cos\theta_{\ell}$, (OS$\mu$, Belle)

Efficiency as function of the helicity angle of the lepton $\cos\theta_{\ell}$, (OS$\mu$, Belle II)

Efficiency as function of the helicity angle of the lepton $\cos\theta_{\ell}$, (SS$e$, Belle)

Efficiency as function of the helicity angle of the lepton $\cos\theta_{\ell}$, (SS$e$, Belle II)

Efficiency as function of the helicity angle of the lepton $\cos\theta_{\ell}$, (SS$\mu$, Belle)

Efficiency as function of the helicity angle of the lepton $\cos\theta_{\ell}$, (SS$\mu$, Belle II)

Efficiency as function of the acoplanarity angle $\phi$, (OS$e$, Belle)

Efficiency as function of the acoplanarity angle $\phi$, (OS$e$, Belle II)

Efficiency as function of the acoplanarity angle $\phi$, (OS$\mu$, Belle)

Efficiency as function of the acoplanarity angle $\phi$, (OS$\mu$, Belle II)

Efficiency as function of the acoplanarity angle $\phi$, (SS$e$, Belle)

Efficiency as function of the acoplanarity angle $\phi$, (SS$e$, Belle II)

Efficiency as function of the acoplanarity angle $\phi$, (SS$\mu$, Belle)

Efficiency as function of the acoplanarity angle $\phi$, (SS$\mu$, Belle II)

Efficiency as function of the four-momentum-transfer $q^{2}$, (OS$e$, Belle)

Efficiency as function of the four-momentum-transfer $q^{2}$, (OS$e$, Belle II)

Efficiency as function of the four-momentum-transfer $q^{2}$, (OS$\mu$, Belle)

Efficiency as function of the four-momentum-transfer $q^{2}$, (OS$\mu$, Belle II)

Efficiency as function of the four-momentum-transfer $q^{2}$, (SS$e$, Belle)

Efficiency as function of the four-momentum-transfer $q^{2}$, (SS$e$, Belle II)

Efficiency as function of the four-momentum-transfer $q^{2}$, (SS$\mu$, Belle)

Efficiency as function of the four-momentum-transfer $q^{2}$, (SS$\mu$, Belle II)

Efficiency as function of the invariant mass squared $m^2(K^{*0}\ell)$, (OS$e$, Belle)

Efficiency as function of the invariant mass squared $m^2(K^{*0}\ell)$, (OS$e$, Belle II)

Efficiency as function of the invariant mass squared $m^2(K^{*0}\ell)$, (OS$\mu$, Belle)

Efficiency as function of the invariant mass squared $m^2(K^{*0}\ell)$, (OS$\mu$, Belle II)

Efficiency as function of the invariant mass squared $m^2(K^{*0}\ell)$, (SS$e$, Belle)

Efficiency as function of the invariant mass squared $m^2(K^{*0}\ell)$, (SS$e$, Belle II)

Efficiency as function of the invariant mass squared $m^2(K^{*0}\ell)$, (SS$\mu$, Belle)

Efficiency as function of the invariant mass squared $m^2(K^{*0}\ell)$, (SS$\mu$, Belle II)

Efficiency as function of the invariant mass squared $m^2(K^{*0}t_{\tau})$, where $t_{\tau}$ is the track from the $\tau$, (OS$e$, Belle)

Efficiency as function of the invariant mass squared $m^2(K^{*0}t_{\tau})$, where $t_{\tau}$ is the track from the $\tau$, (OS$e$, Belle II)

Efficiency as function of the invariant mass squared $m^2(K^{*0}t_{\tau})$, where $t_{\tau}$ is the track from the $\tau$, (OS$\mu$, Belle)

Efficiency as function of the invariant mass squared $m^2(K^{*0}t_{\tau})$, where $t_{\tau}$ is the track from the $\tau$, (OS$\mu$, Belle II)

Efficiency as function of the invariant mass squared $m^2(K^{*0}t_{\tau})$, where $t_{\tau}$ is the track from the $\tau$, (SS$e$, Belle)

Efficiency as function of the invariant mass squared $m^2(K^{*0}t_{\tau})$, where $t_{\tau}$ is the track from the $\tau$, (SS$e$, Belle II)

Efficiency as function of the invariant mass squared $m^2(K^{*0}t_{\tau})$, where $t_{\tau}$ is the track from the $\tau$, (SS$\mu$, Belle)

Efficiency as function of the invariant mass squared $m^2(K^{*0}t_{\tau})$, where $t_{\tau}$ is the track from the $\tau$, (SS$\mu$, Belle II)

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $p_{\mathrm{T}}^{\mathrm{lead.\,lep.}}$.

Fiducial differential cross-sections as a function of $p_{\mathrm{T}}^{\mathrm{sub-lead.\,lep.}}$. The measured cross-section values are shown as points with error bars giving the statistical uncertainty and solid bands indicating the size of the total uncertainty. The right-hand-side axis indicates the integrated cross-section of the rightmost bin. The results are compared to fixed-order nNNLO QCD + NLO EW predictions of Matrix 2.1, with the NNLO + PS predictions from Powheg MiNNLO + Pythia8 and Geneva + Pythia8, as well as Sherpa2.2.12 NLO + PS predictions. The last three predictions are combined with Sherpa 2.2.2 for the $gg$ initial state and Sherpa 2.2.12 for electroweak $WWjj$ production. These contributions are modelled at LO but a NLO QCD $k$-factor of 1.7 is applied for gluon induced production. Theoretical predictions are indicated as markers with vertical lines denoting PDF, scale and parton shower uncertainties. Markers are staggered for better visibility.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $p_{\mathrm{T}}^{\mathrm{sub-lead.\,lep.}}$.

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $p_{\mathrm{T}}^{\mathrm{sub-lead.\,lep.}}$.

Fiducial differential cross-sections as a function of $p_{\mathrm{T},e\mu}$. The measured cross-section values are shown as points with error bars giving the statistical uncertainty and solid bands indicating the size of the total uncertainty. The right-hand-side axis indicates the integrated cross-section of the rightmost bin. The results are compared to fixed-order nNNLO QCD + NLO EW predictions of Matrix 2.1, with the NNLO + PS predictions from Powheg MiNNLO + Pythia8 and Geneva + Pythia8, as well as Sherpa2.2.12 NLO + PS predictions. The last three predictions are combined with Sherpa 2.2.2 for the $gg$ initial state and Sherpa 2.2.12 for electroweak $WWjj$ production. These contributions are modelled at LO but a NLO QCD $k$-factor of 1.7 is applied for gluon induced production. Theoretical predictions are indicated as markers with vertical lines denoting PDF, scale and parton shower uncertainties. Markers are staggered for better visibility.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $p_{\mathrm{T},e\mu}$.

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $p_{\mathrm{T},e\mu}$.

Fiducial differential cross-sections as a function of $|y_{e\mu}|$. The measured cross-section values are shown as points with error bars giving the statistical uncertainty and solid bands indicating the size of the total uncertainty. The results are compared to fixed-order nNNLO QCD + NLO EW predictions of Matrix 2.1, with the NNLO + PS predictions from Powheg MiNNLO + Pythia8 and Geneva + Pythia8, as well as Sherpa2.2.12 NLO + PS predictions. The last three predictions are combined with Sherpa 2.2.2 for the $gg$ initial state and Sherpa 2.2.12 for electroweak $WWjj$ production. These contributions are modelled at LO but a NLO QCD $k$-factor of 1.7 is applied for gluon induced production. Theoretical predictions are indicated as markers with vertical lines denoting PDF, scale and parton shower uncertainties. Markers are staggered for better visibility.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $|y_{e\mu}|$.

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $|y_{e\mu}|$.

Fiducial differential cross-sections as a function of $m_{e\mu}$. The measured cross-section values are shown as points with error bars giving the statistical uncertainty and solid bands indicating the size of the total uncertainty. The right-hand-side axis indicates the integrated cross-section of the rightmost bin. The results are compared to fixed-order nNNLO QCD + NLO EW predictions of Matrix 2.1, with the NNLO + PS predictions from Powheg MiNNLO + Pythia8 and Geneva + Pythia8, as well as Sherpa2.2.12 NLO + PS predictions. The last three predictions are combined with Sherpa 2.2.2 for the $gg$ initial state and Sherpa 2.2.12 for electroweak $WWjj$ production. These contributions are modelled at LO but a NLO QCD $k$-factor of 1.7 is applied for gluon induced production. Theoretical predictions are indicated as markers with vertical lines denoting PDF, scale and parton shower uncertainties. Markers are staggered for better visibility.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $m_{e\mu}$.

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $m_{e\mu}$.

Fiducial differential cross-sections as a function of $|\Delta\phi_{e\mu}|$. The measured cross-section values are shown as points with error bars giving the statistical uncertainty and solid bands indicating the size of the total uncertainty. The results are compared to fixed-order nNNLO QCD + NLO EW predictions of Matrix 2.1, with the NNLO + PS predictions from Powheg MiNNLO + Pythia8 and Geneva + Pythia8, as well as Sherpa2.2.12 NLO + PS predictions. The last three predictions are combined with Sherpa 2.2.2 for the $gg$ initial state and Sherpa 2.2.12 for electroweak $WWjj$ production. These contributions are modelled at LO but a NLO QCD $k$-factor of 1.7 is applied for gluon induced production. Theoretical predictions are indicated as markers with vertical lines denoting PDF, scale and parton shower uncertainties. Markers are staggered for better visibility.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $|\Delta\phi_{e\mu}|$.

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $|\Delta\phi_{e\mu}|$.

Fiducial differential cross-sections as a function of $\cos(\theta^{*})$. The measured cross-section values are shown as points with error bars giving the statistical uncertainty and solid bands indicating the size of the total uncertainty. The results are compared to fixed-order nNNLO QCD + NLO EW predictions of Matrix 2.1, with the NNLO + PS predictions from Powheg MiNNLO + Pythia8 and Geneva + Pythia8, as well as Sherpa2.2.12 NLO + PS predictions. The last three predictions are combined with Sherpa 2.2.2 for the $gg$ initial state and Sherpa 2.2.12 for electroweak $WWjj$ production. These contributions are modelled at LO but a NLO QCD $k$-factor of 1.7 is applied for gluon induced production. Theoretical predictions are indicated as markers with vertical lines denoting PDF, scale and parton shower uncertainties. Markers are staggered for better visibility.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $\cos(\theta^{*})$.

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $\cos(\theta^{*})$.

Fiducial differential cross-sections as a function of $E_{\mathrm{T}}^{\mathrm{miss}}$. The measured cross-section values are shown as points with error bars giving the statistical uncertainty and solid bands indicating the size of the total uncertainty. The right-hand-side axis indicates the integrated cross-section of the rightmost bin. The results are compared to fixed-order nNNLO QCD + NLO EW predictions of Matrix 2.1, with the NNLO + PS predictions from Powheg MiNNLO + Pythia8 and Geneva + Pythia8, as well as Sherpa2.2.12 NLO + PS predictions. The last three predictions are combined with Sherpa 2.2.2 for the $gg$ initial state and Sherpa 2.2.12 for electroweak $WWjj$ production. These contributions are modelled at LO but a NLO QCD $k$-factor of 1.7 is applied for gluon induced production. Theoretical predictions are indicated as markers with vertical lines denoting PDF, scale and parton shower uncertainties. Markers are staggered for better visibility.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $E_{\mathrm{T}}^{\mathrm{miss}}$.

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $E_{\mathrm{T}}^{\mathrm{miss}}$.

Fiducial differential cross-sections as a function of $H_{\mathrm{T}}^{\mathrm{lep}+\mathrm{MET}}$. The measured cross-section values are shown as points with error bars giving the statistical uncertainty and solid bands indicating the size of the total uncertainty. The right-hand-side axis indicates the integrated cross-section of the rightmost bin. The results are compared to fixed-order nNNLO QCD + NLO EW predictions of Matrix 2.1, with the NNLO + PS predictions from Powheg MiNNLO + Pythia8 and Geneva + Pythia8, as well as Sherpa2.2.12 NLO + PS predictions. The last three predictions are combined with Sherpa 2.2.2 for the $gg$ initial state and Sherpa 2.2.12 for electroweak $WWjj$ production. These contributions are modelled at LO but a NLO QCD $k$-factor of 1.7 is applied for gluon induced production. Theoretical predictions are indicated as markers with vertical lines denoting PDF, scale and parton shower uncertainties. Markers are staggered for better visibility.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $H_{\mathrm{T}}^{\mathrm{lep}+\mathrm{MET}}$.

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $H_{\mathrm{T}}^{\mathrm{lep}+\mathrm{MET}}$.

Fiducial differential cross-sections as a function of $m_{\mathrm{T},e\mu}$. The measured cross-section values are shown as points with error bars giving the statistical uncertainty and solid bands indicating the size of the total uncertainty. The right-hand-side axis indicates the integrated cross-section of the rightmost bin. The results are compared to fixed-order nNNLO QCD + NLO EW predictions of Matrix 2.1, with the NNLO + PS predictions from Powheg MiNNLO + Pythia8 and Geneva + Pythia8, as well as Sherpa2.2.12 NLO + PS predictions. The last three predictions are combined with Sherpa 2.2.2 for the $gg$ initial state and Sherpa 2.2.12 for electroweak $WWjj$ production. These contributions are modelled at LO but a NLO QCD $k$-factor of 1.7 is applied for gluon induced production. Theoretical predictions are indicated as markers with vertical lines denoting PDF, scale and parton shower uncertainties. Markers are staggered for better visibility.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $m_{\mathrm{T},e\mu}$.

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $m_{\mathrm{T},e\mu}$.

Fiducial differential cross-sections as a function of the number of jets. The measured cross-section values are shown as points with error bars giving the statistical uncertainty and solid bands indicating the size of the total uncertainty. The results are compared to fixed-order nNNLO QCD + NLO EW predictions of Matrix 2.1, with the NNLO + PS predictions from Powheg MiNNLO + Pythia8 and Geneva + Pythia8, as well as Sherpa2.2.12 NLO + PS predictions. The last three predictions are combined with Sherpa 2.2.2 for the $gg$ initial state and Sherpa 2.2.12 for electroweak $WWjj$ production. These contributions are modelled at LO but a NLO QCD $k$-factor of 1.7 is applied for gluon induced production. Theoretical predictions are indicated as markers with vertical lines denoting PDF, scale and parton shower uncertainties. Markers are staggered for better visibility.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable Number of jets ($p_{\mathrm{T}} > $ 30 GeV).

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable Number of jets ($p_{\mathrm{T}} > $ 30 GeV).

Fiducial differential cross-sections as a function of $S_{\mathrm{T}}$. The measured cross-section values are shown as points with error bars giving the statistical uncertainty and solid bands indicating the size of the total uncertainty. The right-hand-side axis indicates the integrated cross-section of the rightmost bin. The results are compared to fixed-order nNNLO QCD + NLO EW predictions of Matrix 2.1, with the NNLO + PS predictions from Powheg MiNNLO + Pythia8 and Geneva + Pythia8, as well as Sherpa2.2.12 NLO + PS predictions. The last three predictions are combined with Sherpa 2.2.2 for the $gg$ initial state and Sherpa 2.2.12 for electroweak $WWjj$ production. These contributions are modelled at LO but a NLO QCD $k$-factor of 1.7 is applied for gluon induced production. Theoretical predictions are indicated as markers with vertical lines denoting PDF, scale and parton shower uncertainties. Markers are staggered for better visibility.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $S_{\mathrm{T}}$.

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $S_{\mathrm{T}}$.

Fiducial differential cross-sections for $p_{\mathrm{T},e\mu}$ in the region with 85 $<m_{e\mu}<$ 150, for the nNNLO MATRIX prediction and various four flavour PDF sets. The measured cross-section values are shown as points with error bars giving the statistical uncertainty and solid bands indicating the size of the total uncertainty. The right-hand-side axis indicates the integrated cross-section of the rightmost bin. The measurement is compared to fixed-order nNNLO QCD + NLO EW predictions of Matrix 2.1 using four different four-flavour NNLO PDF sets: NNPDF3.0, NNPDF3.1, CT18, and MSHT20.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $p_{\mathrm{T},e\mu}$ (85 $<m_{e\mu}<$ 150).

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $p_{\mathrm{T},e\mu}$ (85 $<m_{e\mu}<$ 150).

Fiducial differential cross-sections for $|y_{e\mu}|$ in the region with 85 $<m_{e\mu}<$ 150, for the nNNLO MATRIX prediction and various four flavour PDF sets. The measured cross-section values are shown as points with error bars giving the statistical uncertainty and solid bands indicating the size of the total uncertainty. The measurement is compared to fixed-order nNNLO QCD + NLO EW predictions of Matrix 2.1 using four different four-flavour NNLO PDF sets: NNPDF3.0, NNPDF3.1, CT18, and MSHT20.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $|y_{e\mu}|$ (85 $<m_{e\mu}<$ 150).

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $|y_{e\mu}|$ (85 $<m_{e\mu}<$ 150).

Fiducial differential cross-sections for $p_{\mathrm{T},e\mu}$ in the region with 150 $<m_{e\mu}<$ 250, for the nNNLO MATRIX prediction and various four flavour PDF sets. The measured cross-section values are shown as points with error bars giving the statistical uncertainty and solid bands indicating the size of the total uncertainty. The right-hand-side axis indicates the integrated cross-section of the rightmost bin. The measurement is compared to fixed-order nNNLO QCD + NLO EW predictions of Matrix 2.1 using four different four-flavour NNLO PDF sets: NNPDF3.0, NNPDF3.1, CT18, and MSHT20.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $p_{\mathrm{T},e\mu}$ (150 $<m_{e\mu}<$ 250).

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $p_{\mathrm{T},e\mu}$ (150 $<m_{e\mu}<$ 250).

Fiducial differential cross-sections for $|y_{e\mu}|$ in the region with 150 $<m_{e\mu}<$ 250, for the nNNLO MATRIX prediction and various four flavour PDF sets. The measured cross-section values are shown as points with error bars giving the statistical uncertainty and solid bands indicating the size of the total uncertainty. The measurement is compared to fixed-order nNNLO QCD + NLO EW predictions of Matrix 2.1 using four different four-flavour NNLO PDF sets: NNPDF3.0, NNPDF3.1, CT18, and MSHT20.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $|y_{e\mu}|$ (150 $<m_{e\mu}<$ 250).

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $|y_{e\mu}|$ (150 $<m_{e\mu}<$ 250).

Fiducial differential cross-sections for $p_{\mathrm{T},e\mu}$ in the region with $m_{e\mu}>$ 250, for the nNNLO MATRIX prediction and various four flavour PDF sets. The measured cross-section values are shown as points with error bars giving the statistical uncertainty and solid bands indicating the size of the total uncertainty. The right-hand-side axis indicates the integrated cross-section of the rightmost bin. The measurement is compared to fixed-order nNNLO QCD + NLO EW predictions of Matrix 2.1 using four different four-flavour NNLO PDF sets: NNPDF3.0, NNPDF3.1, CT18, and MSHT20.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $p_{\mathrm{T},e\mu}$ ($m_{e\mu}>$ 250).

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $p_{\mathrm{T},e\mu}$ ($m_{e\mu}>$ 250).

Fiducial differential cross-sections for $|y_{e\mu}|$ in the region with $m_{e\mu}>$ 250, for the nNNLO MATRIX prediction and various four flavour PDF sets. The measured cross-section values are shown as points with error bars giving the statistical uncertainty and solid bands indicating the size of the total uncertainty. The measurement is compared to fixed-order nNNLO QCD + NLO EW predictions of Matrix 2.1 using four different four-flavour NNLO PDF sets: NNPDF3.0, NNPDF3.1, CT18, and MSHT20.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $|y_{e\mu}|$ ($m_{e\mu}>$ 250).

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $|y_{e\mu}|$ ($m_{e\mu}>$ 250).

Measured value of the charge asymmetry, $A_{C}$.

Charge asymmetry $A_C$ measured as a function of the absolute difference of the absolute lepton rapidities $||\eta_{l+}|-|\eta_{l-}||$. The measured values are shown as points, whose error bars represent the statistical uncertainty, while the solid bands indicate the size of the total uncertainty. In the bottom panel, the central value of the charge asymmetry divided by the total uncertainty of the $A_C$ measurement is shown. The measurement is compared with the NNLO+PS predictions from Powheg MiNNLO+Pythia8 with vertical lines denoting PDF uncertainties.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $A_{C}$ vs. $||\eta_{l+}|-|\eta_{l-}||$.

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $A_{C}$ vs. $||\eta_{l+}|-|\eta_{l-}||$.

Charge asymmetry $A_C$ measured as a function of the invariant mass of the dilepton system $m_{e\mu}$. The measured values are shown as points, whose error bars represent the statistical uncertainty, while the solid bands indicate the size of the total uncertainty. In the bottom panel, the central value of the charge asymmetry divided by the total uncertainty of the $A_C$ measurement is shown. The measurement is compared with the NNLO+PS predictions from Powheg MiNNLO+Pythia8 with vertical lines denoting PDF uncertainties.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $A_{C}$ vs. $m_{e\mu}$.

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $A_{C}$ vs. $m_{e\mu}$.

Measured value of the asymmetry in the CP-odd observable $O_{z}$, $A_{CP}$.

Groomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet,gr}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data, without any WTA flavour requirement. Normalization is set to unity. $20 < p_{\textrm{T,jet}} < 30$ GeV, soft drop $z_{\textrm{cut}}=0.1, \beta=0$.

Groomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet,gr}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data, without any WTA flavour requirement. Normalization is set to unity. $30 < p_{\textrm{T,jet}} < 50$ GeV, soft drop $z_{\textrm{cut}}=0.1, \beta=0$.

Groomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet,gr}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data, without any WTA flavour requirement. Normalization is set to unity. $50 < p_{\textrm{T,jet}} < 100$ GeV, soft drop $z_{\textrm{cut}}=0.1, \beta=0$.

Groomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet,gr}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data, without any WTA flavour requirement. Normalization is set to the soft drop tagging fraction, given by the number of groomed jets (without any WTA flavour requirement) to number of ungroomed jets (without any WTA flavour requirement). $10 < p_{\textrm{T,jet}} < 12$ GeV, soft drop $z_{\textrm{cut}}=0.1, \beta=0$.

Groomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet,gr}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data, without any WTA flavour requirement. Normalization is set to the soft drop tagging fraction, given by the number of groomed jets (without any WTA flavour requirement) to number of ungroomed jets (without any WTA flavour requirement). $12 < p_{\textrm{T,jet}} < 15$ GeV, soft drop $z_{\textrm{cut}}=0.1, \beta=0$.

Groomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet,gr}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data, without any WTA flavour requirement. Normalization is set to the soft drop tagging fraction, given by the number of groomed jets (without any WTA flavour requirement) to number of ungroomed jets (without any WTA flavour requirement). $15 < p_{\textrm{T,jet}} < 20$ GeV, soft drop $z_{\textrm{cut}}=0.1, \beta=0$.

Groomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet,gr}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data, without any WTA flavour requirement. Normalization is set to the soft drop tagging fraction, given by the number of groomed jets (without any WTA flavour requirement) to number of ungroomed jets (without any WTA flavour requirement). $20 < p_{\textrm{T,jet}} < 30$ GeV, soft drop $z_{\textrm{cut}}=0.1, \beta=0$.

Groomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet,gr}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data, without any WTA flavour requirement. Normalization is set to the soft drop tagging fraction, given by the number of groomed jets (without any WTA flavour requirement) to number of ungroomed jets (without any WTA flavour requirement). $30 < p_{\textrm{T,jet}} < 50$ GeV, soft drop $z_{\textrm{cut}}=0.1, \beta=0$.

Groomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet,gr}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data, without any WTA flavour requirement. Normalization is set to the soft drop tagging fraction, given by the number of groomed jets (without any WTA flavour requirement) to number of ungroomed jets (without any WTA flavour requirement). $50 < p_{\textrm{T,jet}} < 100$ GeV, soft drop $z_{\textrm{cut}}=0.1, \beta=0$.

Ungroomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data, without any WTA flavour requirement. Normalization is set to unity. $10 < p_{\textrm{T,jet}} < 12$ GeV.

Ungroomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data, without any WTA flavour requirement. Normalization is set to unity. $12 < p_{\textrm{T,jet}} < 15$ GeV.

Ungroomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data, without any WTA flavour requirement. Normalization is set to unity. $15 < p_{\textrm{T,jet}} < 20$ GeV.

Ungroomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data, without any WTA flavour requirement. Normalization is set to unity. $20 < p_{\textrm{T,jet}} < 30$ GeV.

Ungroomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data, without any WTA flavour requirement. Normalization is set to unity. $30 < p_{\textrm{T,jet}} < 50$ GeV.

Ungroomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data, without any WTA flavour requirement. Normalization is set to unity. $50 < p_{\textrm{T,jet}} < 100$ GeV.

Groomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet,gr}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data tagged with WTA flavour. Normalization is set to the WTA tagging fraction, given by the number of (groomed) jets tagged with WTA flavour to number of (groomed) jets without WTA flavour tagging. $10 < p_{\textrm{T,jet}} < 12$ GeV, soft drop $z_{\textrm{cut}}=0.1, \beta=0$.

Groomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet,gr}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data tagged with WTA flavour. Normalization is set to the WTA tagging fraction, given by the number of (groomed) jets tagged with WTA flavour to number of (groomed) jets without WTA flavour tagging. $12 < p_{\textrm{T,jet}} < 15$ GeV, soft drop $z_{\textrm{cut}}=0.1, \beta=0$.

Groomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet,gr}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data tagged with WTA flavour. Normalization is set to the WTA tagging fraction, given by the number of (groomed) jets tagged with WTA flavour to number of (groomed) jets without WTA flavour tagging. $15 < p_{\textrm{T,jet}} < 20$ GeV, soft drop $z_{\textrm{cut}}=0.1, \beta=0$.

Groomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet,gr}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data tagged with WTA flavour. Normalization is set to the WTA tagging fraction, given by the number of (groomed) jets tagged with WTA flavour to number of (groomed) jets without WTA flavour tagging. $20 < p_{\textrm{T,jet}} < 30$ GeV, soft drop $z_{\textrm{cut}}=0.1, \beta=0$.

Groomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet,gr}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data tagged with WTA flavour. Normalization is set to the WTA tagging fraction, given by the number of (groomed) jets tagged with WTA flavour to number of (groomed) jets without WTA flavour tagging. $30 < p_{\textrm{T,jet}} < 50$ GeV, soft drop $z_{\textrm{cut}}=0.1, \beta=0$.

Groomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet,gr}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data tagged with WTA flavour. Normalization is set to the WTA tagging fraction, given by the number of (groomed) jets tagged with WTA flavour to number of (groomed) jets without WTA flavour tagging. $50 < p_{\textrm{T,jet}} < 100$ GeV, soft drop $z_{\textrm{cut}}=0.1, \beta=0$.

Groomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet,gr}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data tagged with WTA flavour. Normalization is set to the soft drop tagging fraction, given by the number of groomed jets (tagged with WTA flavour) to number of ungroomed jets (tagged with WTA flavour). $10 < p_{\textrm{T,jet}} < 12$ GeV, soft drop $z_{\textrm{cut}}=0.1, \beta=0$.

Groomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet,gr}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data tagged with WTA flavour. Normalization is set to the soft drop tagging fraction, given by the number of groomed jets (tagged with WTA flavour) to number of ungroomed jets (tagged with WTA flavour). $12 < p_{\textrm{T,jet}} < 15$ GeV, soft drop $z_{\textrm{cut}}=0.1, \beta=0$.

Groomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet,gr}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data tagged with WTA flavour. Normalization is set to the soft drop tagging fraction, given by the number of groomed jets (tagged with WTA flavour) to number of ungroomed jets (tagged with WTA flavour). $15 < p_{\textrm{T,jet}} < 20$ GeV, soft drop $z_{\textrm{cut}}=0.1, \beta=0$.

Groomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet,gr}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data tagged with WTA flavour. Normalization is set to the soft drop tagging fraction, given by the number of groomed jets (tagged with WTA flavour) to number of ungroomed jets (tagged with WTA flavour). $20 < p_{\textrm{T,jet}} < 30$ GeV, soft drop $z_{\textrm{cut}}=0.1, \beta=0$.

Groomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet,gr}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data tagged with WTA flavour. Normalization is set to the soft drop tagging fraction, given by the number of groomed jets (tagged with WTA flavour) to number of ungroomed jets (tagged with WTA flavour). $30 < p_{\textrm{T,jet}} < 50$ GeV, soft drop $z_{\textrm{cut}}=0.1, \beta=0$.

Groomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet,gr}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data tagged with WTA flavour. Normalization is set to the soft drop tagging fraction, given by the number of groomed jets (tagged with WTA flavour) to number of ungroomed jets (tagged with WTA flavour). $50 < p_{\textrm{T,jet}} < 100$ GeV, soft drop $z_{\textrm{cut}}=0.1, \beta=0$.

Ungroomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data tagged with WTA flavour. Normalization is set to the WTA tagging fraction, given by the number of (ungroomed) jets tagged with WTA flavour to number of (ungroomed) jets without WTA flavour tagging. $10 < p_{\textrm{T,jet}} < 12$ GeV.

Ungroomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data tagged with WTA flavour. Normalization is set to the WTA tagging fraction, given by the number of (ungroomed) jets tagged with WTA flavour to number of (ungroomed) jets without WTA flavour tagging. $12 < p_{\textrm{T,jet}} < 15$ GeV.

Ungroomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data tagged with WTA flavour. Normalization is set to the WTA tagging fraction, given by the number of (ungroomed) jets tagged with WTA flavour to number of (ungroomed) jets without WTA flavour tagging. $15 < p_{\textrm{T,jet}} < 20$ GeV.

Ungroomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data tagged with WTA flavour. Normalization is set to the WTA tagging fraction, given by the number of (ungroomed) jets tagged with WTA flavour to number of (ungroomed) jets without WTA flavour tagging. $20 < p_{\textrm{T,jet}} < 30$ GeV.

Ungroomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data tagged with WTA flavour. Normalization is set to the WTA tagging fraction, given by the number of (ungroomed) jets tagged with WTA flavour to number of (ungroomed) jets without WTA flavour tagging. $30 < p_{\textrm{T,jet}} < 50$ GeV.

Ungroomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data tagged with WTA flavour. Normalization is set to the WTA tagging fraction, given by the number of (ungroomed) jets tagged with WTA flavour to number of (ungroomed) jets without WTA flavour tagging. $50 < p_{\textrm{T,jet}} < 100$ GeV.

Ungroomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data tagged with WTA flavour. Normalization is set to unity. $10 < p_{\textrm{T,jet}} < 12$ GeV.

Ungroomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data tagged with WTA flavour. Normalization is set to unity. $12 < p_{\textrm{T,jet}} < 15$ GeV.

Ungroomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data tagged with WTA flavour. Normalization is set to unity. $15 < p_{\textrm{T,jet}} < 20$ GeV.

Ungroomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data tagged with WTA flavour. Normalization is set to unity. $20 < p_{\textrm{T,jet}} < 30$ GeV.

Ungroomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data tagged with WTA flavour. Normalization is set to unity. $30 < p_{\textrm{T,jet}} < 50$ GeV.

Ungroomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data tagged with WTA flavour. Normalization is set to unity. $50 < p_{\textrm{T,jet}} < 100$ GeV.