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.

Background-only fit to the observed numbers of events (black points) as a function of the diphoton invariant mass $m_{\gamma\gamma}$.

Expected and observed 95% CL upper limits on the signal fiducial cross section $\sigma_{\textrm{fid}}$, assuming 100% branching ratio for ALP decay into two photons, as a function of the hypothetical ALP mass $m_{\textrm{X}}$. The 1$\sigma$ and 2$\sigma$ confidence intervals are shown by the coloured bands.

Expected and observed 95% CL upper limits on the the ALP coupling constant, assuming 100% branching ratio for ALP decay into two photons, as a function of the hypothetical ALP mass $m_{\textrm{X}}$. The 1$\sigma$ and 2$\sigma$ confidence intervals are shown by the coloured bands. Contours of the ALP natural width $\Gamma$ are illustrated by the smooth blue solid lines.

Fiducial region acceptance of signal events for coupling constant f$^{-1}=0.05$ TeV$^{-1}$. EL, SD, and DD stand for the exclusive, single-dissociative, and double-dissociative processes. The acceptances are parameterised as $p_0 + p^{i}_{1} e^{p_{2}^{i} m_{\textrm{X}}} + p_{3}^{i} e^{p_{4}^{i} m_{\textrm{X}}} $ , where $i$ specifies the process type, exclusive, single-dissociative, or double-dissociative.

Correction factors $A_{\textrm{X}}/A_{0}$ and $C_{\textrm{X}}$ for the exclusive signal events with ALP coupling constant f$^{-1}$=0.05 TeV$^{-1}$, where acceptance $A_{\textrm{X}}$ and efficiency $C_{\textrm{X}}$ are defined in arXiv:2102.13405. $A_{\textrm{X}}$/$A_{0}$ and $C_{\textrm{X}}$ are parameterised as $p_0 + p^{i}_{1} e^{p_{2}^{i} m_{\textrm{X}}} + p_{3}^{i} e^{p_{4}^{i} m_{\textrm{X}}}$, where $i$ specifies the process type.

Simulated ALP signal cutflow for $m_{\rm{X}}$=300 GeV and $m_{\rm{X}}$=1200 GeV. The yields are normalized to a luminosity of 14.6 fb$^{-1}$. Selections are applied for each side after the selection on acoplanarity. The union of the sets of selected events is taken finally.

Figure 4a

Figure 4b

Figure 4c

Figure 5a

Figure 5b

Figure 5c

Figure 7

Figure 8a

Figure 8b

Figure 8c

Figure 9a

Figure 9b

Figure 9c

Figure 10a

Figure 10b

Figure 10c

Expected 95% CL exclusion contours in the $(m(W_{R}), m(N_{R}))$ plane in the muon channel for boosted.

Observed 95% CL exclusion contours for the assumption of Dirac type in the $(m(W_{R}), m(N_{R}))$ plane in the electron channel for boosted.

Expected 95% CL exclusion contours for the assumption of Dirac type in the $(m(W_{R}), m(N_{R}))$ plane in the electron channel for boosted.

Observed 95% CL exclusion contours for the assumpition of Dirac type in the $(m(W_{R}), m(N_{R}))$ plane in the muon channel for boosted.

Expected 95% CL exclusion contours for the assumption of Dirac type in the $(m(W_{R}), m(N_{R}))$ plane in the muon channel for boosted.

Observed 95% CL exclusion contours for the assumption of Majorana type in the $(m(W_{R}), m(N_{R}))$ plane in the electron channel for resolved.

Expected 95% CL exclusion contours for the assumption of Majorana type in the $(m(W_{R}), m(N_{R}))$ plane in the electron channel for resolved.

Observed 95% CL exclusion contours for the assumption of Majorana type in the $(m(W_{R}), m(N_{R}))$ plane in the muon channel for resolved.

Expected 95% CL exclusion contours for the assumption of Majorana type in the $(m(W_{R}), m(N_{R}))$ plane in the muon channel for resolved.

Observed 95% CL exclusion contours for the assumption of Dirac type in the $(m(W_{R}), m(N_{R}))$ plane in the electron channel for resolved.

Expected 95% CL exclusion contours for the assumption of Dirac type in the $(m(W_{R}), m(N_{R}))$ plane in the electron channel for resolved.

Observed 95% CL exclusion contours for the assumption of Dirac type in the $(m(W_{R}), m(N_{R}))$ plane in the muon channel for resolved.

Expected 95% CL exclusion contours for the assumption of Dirac type in the $(m(W_{R}), m(N_{R}))$ plane in the muon channel for resolved.

The $m_{eJ}$ distribution in the boosted one electron channel.

The $m_{eeJ}$ distribution in the boosted two electron channel.

The $m_{\mu\mu J}$ distribution in the boosted two muon channel.

The $m_{jj}$ distribution in the resolved electron channel.

The $m_{jj}$ distribution in the resolved muon channel.

The $m_{eejj}$ distribution in the resolved electron channel.

The $m_{\mu\mu jj}$ distribution in the resolved muon channel.

The $h_{T}$ distribution in the resolved electron channel.

The $h_{T}$ distribution in the resolved muon channel.

Acceptance $\times$ efficiency for bSR1e.

Acceptance $\times$ efficiency for bSR2e.

Acceptance $\times$ efficiency for bSR2mu.

Acceptance $\times$ efficiency for rSROS2e.

Acceptance $\times$ efficiency for rSROS2mu.

Acceptance $\times$ efficiency for rSRSS2e.

Acceptance $\times$ efficiency for rSRSS2mu.

Expected and observed 95% CL upper limits for $\sigma(pp\to W_{R})\times B(W_{R}\to eeqq)$ as a function of $m(W_{R})$ for the special case of $m(W_{R}) = 2\times m(N_{R})$. The theoretical cross section corresponds to either the Dirac or Majorana neutrino interpretation by ignoring the charge of the leptons.

Expected and observed 95% CL upper limits for $\sigma(pp\to W_{R})\times B(W_{R} \to \mu\mu qq)$ as a function of $m(W_{R})$ for the special case of $m(W_{R}) = 2\times m(N_{R})$. The theoretical cross section corresponds to either the Dirac or Majorana neutrino interpretation by ignoring the charge of the leptons.

Expected and observed 95% CL upper limits for $\sigma(pp\to W_{R})\times B(W_{R} \to eeqq)$ as a function of $m(W_{R})$ for the special case of $m(N_{R})=200$ GeV. The theoretical cross section corresponds to either the Dirac or Majorana neutrino interpretation by ignoring the charge of the leptons.

Expected and observed 95% CL upper limits for $\sigma(pp\to W_{R})\times B(W_{R} \to \mu \mu qq)$ as a function of $m(W_{R})$ for the special case of $m(N_{R})=200$ GeV. The theoretical cross section corresponds to either the Dirac or Majorana neutrino interpretation by ignoring the charge of the leptons.

Expected and observed 95% CL upper limits for $\sigma(pp \to W_{R}) \times B(W_{R} \to eeqq)$ as a function of $m(W_{R})$ for the Majorana neutrino interpretations for the special case of $m(W_{R}) = 2\times m(N_{R})$.

Expected and observed 95% CL upper limits for $\sigma(pp \to W_{R}) \times B(W_{R} \to \mu\mu qq)$ as a function of $m(W_{R})$ for the Majorana neutrino interpretations for the special case of $m(W_{R}) = 2 \times m(N_{R})$.

Expected and observed 95% CL upper limits for $\sigma(pp \to W_{R}) \times B(W_{R} \to eeqq)$ as a function of $m(W_{R})$ for the Dirac neutrino interpretations for the special case of $m(W_{R}) = 2 \times m(N_{R})$.

Expected and observed 95% CL upper limits for $\sigma(pp \to W_{R}) \times B(W_{R} \to \mu \mu qq)$ as a function of $m(W_{R})$ for the Dirac neutrino interpretations for the special case of $m(W_{R}) = 2 \times m(N_{R})$.

\Delta v_1 between proton and anti-proton vs rapidity in Au+Au 200 GeV 50-80% centrality.

\Delta v_1 between proton and anti-proton vs rapidity in Zr+Zr and Ru+Ru (combined) 200 GeV 50-80% centrality.

\Delta v_1 between proton and anti-proton vs rapidity in Au+Au 27 GeV 50-80% centrality.

\Delta dv1/dy as a function of centrality in Au+Au 200 GeV.

\Delta dv1/dy as a function of centrality in Ru+Ru and Zr+Zr 200 GeV

\Delta dv1/dy as a function of centrality in Au+Au 27 GeV.

Measured $R_\text{AA}$ for the $\Upsilon(3S)$ state in the 0–90% centrality interval, integrated over the full kinematic range $p_\text{T}$ < 30 GeV/c and |y| < 2.4. The global uncertainty "PP MB" represents the pp luminosity and PbPb $N_\text{MB}$ combined uncertainties, whereas the global uncertainty "PP 3S" corresponds to the uncertainty on the$\Upsilon(3S)$ pp yields.

Measured $R_\text{AA}$ for the $\Upsilon(2S)$ state as functions of transverse momentum $p_\text{T}$, integrated over the rapidity range of |y| < 2.4 and the 0–90% centrality interval. The global uncertainty combines the uncertainties of $T_\text{AA}$ , pp luminosity, and PbPb $N_\text{MB}$.

Measured $R_\text{AA}$ for the $\Upsilon(3S)$ state as functions of transverse momentum $p_\text{T}$, integrated over the rapidity range of |y| < 2.4 and the 0–90% centrality interval. The global uncertainty combines the uncertainties of $T_\text{AA}$ , pp luminosity, and PbPb $N_\text{MB}$.

The double ratios of $\Upsilon(3S)$ /$\Upsilon(2S)$ as functions of PbPb collision centrality, integrated over the full kinematic range $p_\text{T}$ < 30 GeV/c and |y| < 2.4. The global uncertainty represents the combined systematic and statistical uncertainties from pp data.

The double ratios of $\Upsilon(3S)$ /$\Upsilon(2S)$ in the 0–90% centrality interval, integrated over the full kinematic range $p_\text{T}$ < 30 GeV/c and |y| < 2.4. The global uncertainty represents the combined systematic and statistical uncertainties from pp data.

The double ratios of $\Upsilon(3S)$ /$\Upsilon(2S)$ as functions of transverse momentum $p_\text{T}$, integrated over the rapidity range of |y| < 2.4 and the 0–90% centrality interval.

The total coherent $\mathrm{J}/\psi$ photoproduction cross section as a function of photon-nuclear center-of-mass energy per nucleon $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$, measured in PbPb ultra-peripheral collisions at $\sqrt{s_{\mathrm{NN}}}$ = 5.02 TeV. The $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$ values used correspond to the center of each rapidity range. The theoretical uncertainties is due to the uncertainties in the photon flux.

The nuclear gluon suppression factor $R_{\mathrm{g}}^{\mathrm{Pb}}$ as a function of Bjorken $x$ extracted from the CMS measurement of the coherent $\mathrm{J}/\psi$ photoproduction in PbPb ultra-peripheral collisions at $\sqrt{s_{\mathrm{NN}}}$ = 5.02 TeV. The $x$ values are evaluated at the centers of their corresponding rapidity ranges. The theoretical uncertainties are due to the uncertainties in the photon flux and the impulse approximation model.

The nuclear gluon suppression factor $R_{\mathrm{g}}^{\mathrm{Pb}}$ as a function of Bjorken $x$ extracted from the CMS measurement of the coherent $\mathrm{J}/\psi$ photoproduction in PbPb ultra-peripheral collisions at $\sqrt{s_{\mathrm{NN}}}$ = 5.02 TeV. The $x$ values are evaluated at the centers of their corresponding rapidity ranges. The theoretical uncertainties are due to the uncertainties in the photon flux and the impulse approximation model.

The total covariance matrix of the total coherent photoproduction cross section as a function of photon-nuclear center-of-mass energy per nucleon $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$. The covariance matrix includes both the experimental and theoretical (photon flux) uncertainties. The bins are ordered as increasing in $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$.

The photon flux values from STARLight as a function of rapidity, in different neutron multiplicity classes: 0n0n, 0nXn, and XnXn.

The experimental covariance matrix of the total coherent photoproduction cross section as a function of photon-nuclear center-of-mass energy per nucleon $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$. The bins are ordered as increasing in $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$.

The covariance matrix for the flux in the 0n0n neutron multiplicity class.

The theoretical (photon flux) covariance matrix of the total coherent photoproduction cross section as a function of photon-nuclear center-of-mass energy per nucleon $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$. The bins are ordered as increasing in $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$.

The covariance matrix for the flux in the 0nXn neutron multiplicity class.

The covariance matrix for the flux in the XnXn neutron multiplicity class.

The total covariance matrix of the total coherent photoproduction cross section as a function of photon-nuclear center-of-mass energy per nucleon $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$. The covariance matrix includes both the experimental and theoretical (photon flux) uncertainties. The bins are ordered as increasing in $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$.

The experimental covariance matrix of the total coherent photoproduction cross section as a function of photon-nuclear center-of-mass energy per nucleon $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$. The bins are ordered as increasing in $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$.

The theoretical (photon flux) covariance matrix of the total coherent photoproduction cross section as a function of photon-nuclear center-of-mass energy per nucleon $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$. The bins are ordered as increasing in $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$.

Breakdown of systematic uncertainties in the measured inclusive cross-section. The impact of the top-quark mass on the cross-section is included in the table and not counted in the total uncertainty entry in the paper.

Data bootstrap post unfolding for the inclusive cross-section. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. All the provided numbers originate from pseudo-data, including the 0th entry, and are in units of [fb].

Differential absolute cross-section for $\textrm{p}_{\textrm{T}}^{l}$. The impact of the top-quark mass on the cross-section is included in the table and not counted in the total uncertainty entry in the paper. The last bin of the distribution contains the overflow.

Covariance Matrix (statistical uncertainties only) for the differential absolute cross-section for $\textrm{p}_{\textrm{T}}^{l}$. The last bin of the distribution contains the overflow.

Data bootstrap post unfolding for the differential absolute cross-section for $\textrm{p}_{\textrm{T}}^{l}$. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. All the provided numbers originate from pseudo-data, including the 0th entry, and are in units of [fb/GeV]. The last bin of the distribution contains the overflow.

Differential absolute cross-section for $|\eta^{l}|$. The impact of the top-quark mass on the cross-section is included in the table and not counted in the total uncertainty entry in the paper.

Covariance Matrix (statistical uncertainties only) for the differential absolute cross-section for $|\eta^{l}|$.

Data bootstrap post unfolding for the differential absolute cross-section for $|\eta^{l}|$. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. All the provided numbers originate from pseudo-data, including the 0th entry, and are in units of [fb].

Differential absolute cross-section for $\textrm{E}^{e} + \textrm{E}^{\mu}$. The impact of the top-quark mass on the cross-section is included in the table and not counted in the total uncertainty entry in the paper. The last bin of the distribution contains the overflow.

Covariance Matrix (statistical uncertainties only) for the differential absolute cross-section for $\textrm{E}^{e} + \textrm{E}^{\mu}$. The last bin of the distribution contains the overflow.

Data bootstrap post unfolding for the differential absolute cross-section for $\textrm{E}^{e} + \textrm{E}^{\mu}$. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. All the provided numbers originate from pseudo-data, including the 0th entry, and are in units of [fb/GeV]. The last bin of the distribution contains the overflow.

Differential absolute cross-section for $m^{e\mu}$. The impact of the top-quark mass on the cross-section is included in the table and not counted in the total uncertainty entry in the paper. The last bin of the distribution contains the overflow.

Covariance Matrix (statistical uncertainties only) for the differential absolute cross-section for $m^{e\mu}$. The last bin of the distribution contains the overflow.

Data bootstrap post unfolding for the differential absolute cross-section for $m^{e\mu}$. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. All the provided numbers originate from pseudo-data, including the 0th entry, and are in units of [fb/GeV]. The last bin of the distribution contains the overflow.

Differential absolute cross-section for $\textrm{p}_{\textrm{T}}^{e} + \textrm{p}_{\textrm{T}}^{\mu}$. The impact of the top-quark mass on the cross-section is included in the table and not counted in the total uncertainty entry in the paper. The last bin of the distribution contains the overflow.

Covariance Matrix (statistical uncertainties only) for the differential absolute cross-section for $\textrm{p}_{\textrm{T}}^{e} + \textrm{p}_{\textrm{T}}^{\mu}$. The last bin of the distribution contains the overflow.

Data bootstrap post unfolding for the differential absolute cross-section for $\textrm{p}_{\textrm{T}}^{e} + \textrm{p}_{\textrm{T}}^{\mu}$. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. All the provided numbers originate from pseudo-data, including the 0th entry, and are in units of [fb/GeV]. The last bin of the distribution contains the overflow.

Differential absolute cross-section for $\textrm{p}_{\textrm{T}}^{e\mu}$. The impact of the top-quark mass on the cross-section is included in the table and not counted in the total uncertainty entry in the paper. The last bin of the distribution contains the overflow.

Covariance Matrix (statistical uncertainties only) for the differential absolute cross-section for $\textrm{p}_{\textrm{T}}^{e\mu}$. The last bin of the distribution contains the overflow.

Data bootstrap post unfolding for the differential absolute cross-section for $\textrm{p}_{\textrm{T}}^{e\mu}$. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. All the provided numbers originate from pseudo-data, including the 0th entry, and are in units of [fb/GeV]. The last bin of the distribution contains the overflow.

Differential absolute cross-section for $|\Delta\phi^{e\mu}|$. The impact of the top-quark mass on the cross-section is included in the table and not counted in the total uncertainty entry in the paper.

Covariance Matrix (statistical uncertainties only) for the differential absolute cross-section for $|\Delta\phi^{e\mu}|$.

Data bootstrap post unfolding for the differential absolute cross-section for $|\Delta\phi^{e\mu}|$. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. All the provided numbers originate from pseudo-data, including the 0th entry, and are in units of [fb/rad].

Differential absolute cross-section for $|y^{e\mu}|$. The impact of the top-quark mass on the cross-section is included in the table and not counted in the total uncertainty entry in the paper.

Covariance Matrix (statistical uncertainties only) for the differential absolute cross-section for $|y^{e\mu}|$.

Data bootstrap post unfolding for the differential absolute cross-section for $|y^{e\mu}|$. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. All the provided numbers originate from pseudo-data, including the 0th entry, and are in units of [fb].

Double differential absolute cross-section for $|y^{e\mu}|$ x $m^{e\mu}$. The impact of the top-quark mass on the cross-section is included in the table and not counted in the total uncertainty entry in the paper. The highest invariant mass bin of the two distributions contains the overflows.

Covariance Matrix (statistical uncertainties only) for the double differential absolute cross-section for $|y^{e\mu}|$ x $m^{e\mu}$. The highest invariant mass bin of the two distributions contains the overflows.

Data bootstrap post unfolding for the double differential absolute cross-section for $|y^{e\mu}|$ x $m^{e\mu}$. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. All the provided numbers originate from pseudo-data, including the 0th entry, and are in units of [fb/GeV]. The highest invariant mass bin of the two distributions contains the overflows.

Double differential absolute cross-section for $|\Delta\phi^{e\mu}|$ x $m^{e\mu}$. The impact of the top-quark mass on the cross-section is included in the table and not counted in the total uncertainty entry in the paper. The highest invariant mass bin of the two distributions contains the overflows.

Covariance Matrix (statistical uncertainties only) for the double differential absolute cross-section for $|\Delta\phi^{e\mu}|$ x $m^{e\mu}$. The highest invariant mass bin of the two distributions contains the overflows.

Data bootstrap post unfolding for the double differential absolute cross-section for $|\Delta\phi^{e\mu}|$ x $m^{e\mu}$. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. All the provided numbers originate from pseudo-data, including the 0th entry, and are in units of [fb/GeV/rad]. The highest invariant mass bin of the two distributions contains the overflows.

Double differential absolute cross-section for $|\Delta\phi^{e\mu}|$ x $\textrm{p}_{\textrm{T}}^{e\mu}$. The impact of the top-quark mass on the cross-section is included in the table and not counted in the total uncertainty entry in the paper. The highest $\textrm{p}_{\textrm{T}}^{e\mu}$ bin contains the overflows.

Covariance Matrix (statistical uncertainties only) for the double differential absolute cross-section for $|\Delta\phi^{e\mu}|$ x $\textrm{p}_{\textrm{T}}^{e\mu}$. The highest $\textrm{p}_{\textrm{T}}^{e\mu}$ bin contains the overflows.

Data bootstrap post unfolding for the double differential absolute cross-section for $|\Delta\phi^{e\mu}|$ x $\textrm{p}_{\textrm{T}}^{e\mu}$. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. All the provided numbers originate from pseudo-data, including the 0th entry, and are in units of [fb/GeV/rad]. The highest $\textrm{p}_{\textrm{T}}^{e\mu}$ bin contains the overflows.

Double differential absolute cross-section for $|\Delta\phi^{e\mu}|$ x $\textrm{E}^{e} + \textrm{E}^{\mu}$. The impact of the top-quark mass on the cross-section is included in the table and not counted in the total uncertainty entry in the paper. The highest $\textrm{E}^{e} + \textrm{E}^{\mu}$ bin contains the overflows.

Covariance Matrix (statistical uncertainties only) for the double differential absolute cross-section for $|\Delta\phi^{e\mu}|$ x $\textrm{E}^{e} + \textrm{E}^{\mu}$. The highest $\textrm{E}^{e} + \textrm{E}^{\mu}$ bin contains the overflows.

Data bootstrap post unfolding for the double differential absolute cross-section for $|\Delta\phi^{e\mu}|$ x $\textrm{E}^{e} + \textrm{E}^{\mu}$. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. All the provided numbers originate from pseudo-data, including the 0th entry, and are in units of [fb/GeV/rad]. The highest $\textrm{E}^{e} + \textrm{E}^{\mu}$ bin contains the overflows.

Differential normalised cross-section for $\textrm{p}_{\textrm{T}}^{l}$. The impact of the top-quark mass on the cross-section is included in the table and not counted in the total uncertainty entry in the paper. The last bin of the distribution contains the overflow.

Covariance Matrix (statistical uncertainties only) for the differential normalised cross-section for $\textrm{p}_{\textrm{T}}^{l}$. The last bin of the distribution contains the overflow.

Data bootstrap post unfolding for the differential normalised cross-section for $\textrm{p}_{\textrm{T}}^{l}$. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. All the provided numbers originate from pseudo-data, including the 0th entry, and are in units of [1/GeV]. The last bin of the distribution contains the overflow.

Differential normalised cross-section for $|\eta^{l}|$. The impact of the top-quark mass on the cross-section is included in the table and not counted in the total uncertainty entry in the paper.

Covariance Matrix (statistical uncertainties only) for the differential normalised cross-section for $|\eta^{l}|$.

Data bootstrap post unfolding for the differential normalised cross-section for $|\eta^{l}|$. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. All the provided numbers originate from pseudo-data, including the 0th entry.

Differential normalised cross-section for $\textrm{E}^{e} + \textrm{E}^{\mu}$. The impact of the top-quark mass on the cross-section is included in the table and not counted in the total uncertainty entry in the paper. The last bin of the distribution contains the overflow.

Covariance Matrix (statistical uncertainties only) for the differential normalised cross-section for $\textrm{E}^{e} + \textrm{E}^{\mu}$. The last bin of the distribution contains the overflow.

Data bootstrap post unfolding for the differential normalised cross-section for $\textrm{E}^{e} + \textrm{E}^{\mu}$. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. All the provided numbers originate from pseudo-data, including the 0th entry. The last bin of the distribution contains the overflow.

Differential normalised cross-section for $m^{e\mu}$. The impact of the top-quark mass on the cross-section is included in the table and not counted in the total uncertainty entry in the paper. The last bin of the distribution contains the overflow.

Covariance Matrix (statistical uncertainties only) for the differential normalised cross-section for $m^{e\mu}$. The last bin of the distribution contains the overflow.

Data bootstrap post unfolding for the differential normalised cross-section for $m^{e\mu}$. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. All the provided numbers originate from pseudo-data, including the 0th entry. The last bin of the distribution contains the overflow.

Differential normalised cross-section for $\textrm{p}_{\textrm{T}}^{e} + \textrm{p}_{\textrm{T}}^{\mu}$. The impact of the top-quark mass on the cross-section is included in the table and not counted in the total uncertainty entry in the paper. The last bin of the distribution contains the overflow.

Covariance Matrix (statistical uncertainties only) for the differential normalised cross-section for $\textrm{p}_{\textrm{T}}^{e} + \textrm{p}_{\textrm{T}}^{\mu}$. The last bin of the distribution contains the overflow.

Data bootstrap post unfolding for the differential normalised cross-section for $\textrm{p}_{\textrm{T}}^{e} + \textrm{p}_{\textrm{T}}^{\mu}$. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. All the provided numbers originate from pseudo-data, including the 0th entry, and are in units of [1/GeV]. The last bin of the distribution contains the overflow.

Differential normalised cross-section for $\textrm{p}_{\textrm{T}}^{e\mu}$. The impact of the top-quark mass on the cross-section is included in the table and not counted in the total uncertainty entry in the paper. The last bin of the distribution contains the overflow.

Covariance Matrix (statistical uncertainties only) for the differential normalised cross-section for $\textrm{p}_{\textrm{T}}^{e\mu}$. The last bin of the distribution contains the overflow.

Data bootstrap post unfolding for the differential normalised cross-section for $\textrm{p}_{\textrm{T}}^{e\mu}$. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. All the provided numbers originate from pseudo-data, including the 0th entry, and are in units of [1/GeV]. The last bin of the distribution contains the overflow.

Differential normalised cross-section for $|\Delta\phi^{e\mu}|$. The impact of the top-quark mass on the cross-section is included in the table and not counted in the total uncertainty entry in the paper.

Covariance Matrix (statistical uncertainties only) for the differential normalised cross-section for $|\Delta\phi^{e\mu}|$.

Data bootstrap post unfolding for the differential normalised cross-section for $|\Delta\phi^{e\mu}|$. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. All the provided numbers originate from pseudo-data, including the 0th entry, and are in units of [1/rad].

Differential normalised cross-section for $|y^{e\mu}|$. The impact of the top-quark mass on the cross-section is included in the table and not counted in the total uncertainty entry in the paper.

Covariance Matrix (statistical uncertainties only) for the differential normalised cross-section for $|y^{e\mu}|$.

Data bootstrap post unfolding for the differential normalised cross-section for $|y^{e\mu}|$. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. All the provided numbers originate from pseudo-data, including the 0th entry.

Double differential normalised cross-section for $|y^{e\mu}|$ x $m^{e\mu}$. The impact of the top-quark mass on the cross-section is included in the table and not counted in the total uncertainty entry in the paper. The highest invariant mass bin of the two distributions contains the overflows.

Covariance Matrix (statistical uncertainties only) for the double differential normalised cross-section for $|y^{e\mu}|$ x $m^{e\mu}$. The highest invariant mass bin of the two distributions contains the overflows.

Data bootstrap post unfolding for the double differential normalised cross-section for $|y^{e\mu}|$ x $m^{e\mu}$. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. All the provided numbers originate from pseudo-data, including the 0th entry, and are in units of [1/GeV]. The highest invariant mass bin of the two distributions contains the overflows.

Double differential normalised cross-section for $|\Delta\phi^{e\mu}|$ x $m^{e\mu}$. The impact of the top-quark mass on the cross-section is included in the table and not counted in the total uncertainty entry in the paper. The highest invariant mass bin of the two distributions contains the overflows.

Covariance Matrix (statistical uncertainties only) for the double differential normalised cross-section for $|\Delta\phi^{e\mu}|$ x $m^{e\mu}$. The highest invariant mass bin of the two distributions contains the overflows.

Data bootstrap post unfolding for the double differential normalised cross-section for $|\Delta\phi^{e\mu}|$ x $m^{e\mu}$. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. All the provided numbers originate from pseudo-data, including the 0th entry, and are in units of [1/GeV/rad]. The highest invariant mass bin of the two distributions contains the overflows.

Double differential normalised cross-section for $|\Delta\phi^{e\mu}|$ x $\textrm{p}_{\textrm{T}}^{e\mu}$. The impact of the top-quark mass on the cross-section is included in the table and not counted in the total uncertainty entry in the paper. The highest $\textrm{p}_{\textrm{T}}^{e\mu}$ bin contains the overflows.

Covariance Matrix (statistical uncertainties only) for the double differential normalised cross-section for $|\Delta\phi^{e\mu}|$ x $\textrm{p}_{\textrm{T}}^{e\mu}$. The highest $\textrm{p}_{\textrm{T}}^{e\mu}$ bin contains the overflows.

Data bootstrap post unfolding for the double differential normalised cross-section for $|\Delta\phi^{e\mu}|$ x $\textrm{p}_{\textrm{T}}^{e\mu}$. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. All the provided numbers originate from pseudo-data, including the 0th entry, and are in units of [1/GeV/rad]. The highest $\textrm{p}_{\textrm{T}}^{e\mu}$ bin contains the overflows.

Double differential normalised cross-section for $|\Delta\phi^{e\mu}|$ x $\textrm{E}^{e} + \textrm{E}^{\mu}$. The impact of the top-quark mass on the cross-section is included in the table and not counted in the total uncertainty entry in the paper. The highest $\textrm{E}^{e} + \textrm{E}^{\mu}$ bin contains the overflows.

Covariance Matrix (statistical uncertainties only) for the double differential normalised cross-section for $|\Delta\phi^{e\mu}|$ x $\textrm{E}^{e} + \textrm{E}^{\mu}$. The highest $\textrm{E}^{e} + \textrm{E}^{\mu}$ bin contains the overflows.

Data bootstrap post unfolding for the double differential normalised cross-section for $|\Delta\phi^{e\mu}|$ x $\textrm{E}^{e} + \textrm{E}^{\mu}$. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. All the provided numbers originate from pseudo-data, including the 0th entry, and are in units of [1/GeV/rad]. The highest $\textrm{E}^{e} + \textrm{E}^{\mu}$ bin contains the overflows.

Self-normalised yield of electrons from heavy-flavour hadron decays as a function of normalised charged-particle pseudorapidity density at midrapidity computed in pp collisions at $\sqrt{s}$ = 13 TeV in different $p_{\rm T}$ intervals

Self-normalised yield of electrons from heavy-flavour hadron decays as a function of normalised charged-particle pseudorapidity density at midrapidity computed in p--pPb collisions at $\sqrt{s_{\rm NN}}$ = 8.16 TeV in different $p_{\rm T}$ intervals