Charged-hadron pseudorapidity density in XeXe collisions at $\sqrt{s_{NN}} = 5.44$ TeV at midrapidity, normalised by $2A$, where $A$ is the atomic number of the nuclei, as a function of event centrality. The total uncertainty is dominated by the systematic uncertainty, and statistical uncertainties are negligible.

Average charged-hadron pseudorapidity density at midrapidity normalised by $\langle N_{part} \rangle$, shown as a function of $\langle N_{part} \rangle$. The total uncertainty is dominated by the systematic uncertainty, and statistical uncertainties are negligible.

Average charged-hadron pseudorapidity density at midrapidity normalised by $\langle N_{part} \rangle$, shown as a function of $\langle N_{part} \rangle/2A$, where $A$ is the atomic number of the nuclei. The total uncertainty is dominated by the systematic uncertainty, and statistical uncertainties are negligible.

Average charged-hadron pseudorapidity density at midrapidity normalised by $2A$, shown as a function of $\langle N_{part} \rangle/2A$, where $A$ is the atomic number of the nuclei. The total uncertainty is dominated by the systematic uncertainty, and statistical uncertainties are negligible.

Sequential impact of each requirement on the number of events passing the selection for the high-$E_T$ analysis.

Sequential impact of each requirement on the number of events passing the selection for the low-$E_T$ analysis.

Application of the modified ABCD method to the final high-$E_T$ and low-$E_T$ selections.

The extrapolated signal efficiencies as a function of proper decay length of the $s$ for several simulated samples in the low-$E_T$ selections.

The extrapolated signal efficiencies as a function of proper decay length of the $s$ for several simulated samples in the high-$E_T$ selections.

The observed limits, expected limits and $\pm 1 \sigma$ and $\pm 2 \sigma$ bands for a model with $m_{\phi} = 125 ~\mathrm{GeV}$ and $m_{s} = 25 ~\mathrm{GeV}$.

The observed limits, expected limits and $\pm 1 \sigma$ and $\pm 2 \sigma$ bands for a model with $m_{\phi} = 600 ~\mathrm{GeV}$ and $m_{s} = 150 ~\mathrm{GeV}$.

Combined limits for the CalRatio and MS analyses, for a model with $m_{\phi} = 125 ~\mathrm{GeV}$ and $m_{s} = 25 ~\mathrm{GeV}$.

Combined limits for the CalRatio and MS analyses, for a model with $m_{\phi} = 600 ~\mathrm{GeV}$ and $m_{s} = 150 ~\mathrm{GeV}$.

The observed limits, expected limits and $\pm 1 \sigma$ and $\pm 2 \sigma$ bands for a model with $m_{\phi} = 125 ~\mathrm{GeV}$ and $m_{s} = 5 ~\mathrm{GeV}$.

The observed limits, expected limits and $\pm 1 \sigma$ and $\pm 2 \sigma$ bands for a model with $m_{\phi} = 125 ~\mathrm{GeV}$ and $m_{s} = 8 ~\mathrm{GeV}$.

The observed limits, expected limits and $\pm 1 \sigma$ and $\pm 2 \sigma$ bands for a model with $m_{\phi} = 125 ~\mathrm{GeV}$ and $m_{s} = 15 ~\mathrm{GeV}$.

The observed limits, expected limits and $\pm 1 \sigma$ and $\pm 2 \sigma$ bands for a model with $m_{\phi} = 125 ~\mathrm{GeV}$ and $m_{s} = 40 ~\mathrm{GeV}$.

The observed limits, expected limits and $\pm 1 \sigma$ and $\pm 2 \sigma$ bands for a model with $m_{\phi} = 125 ~\mathrm{GeV}$ and $m_{s} = 55 ~\mathrm{GeV}$.

The observed limits, expected limits and $\pm 1 \sigma$ and $\pm 2 \sigma$ bands for a model with $m_{\phi} = 200 ~\mathrm{GeV}$ and $m_{s} = 8 ~\mathrm{GeV}$.

The observed limits, expected limits and $\pm 1 \sigma$ and $\pm 2 \sigma$ bands for a model with $m_{\phi} = 200 ~\mathrm{GeV}$ and $m_{s} = 25 ~\mathrm{GeV}$.

The observed limits, expected limits and $\pm 1 \sigma$ and $\pm 2 \sigma$ bands for a model with $m_{\phi} = 200 ~\mathrm{GeV}$ and $m_{s} = 50 ~\mathrm{GeV}$.

The observed limits, expected limits and $\pm 1 \sigma$ and $\pm 2 \sigma$ bands for a model with $m_{\phi} = 400 ~\mathrm{GeV}$ and $m_{s} = 50 ~\mathrm{GeV}$.

The observed limits, expected limits and $\pm 1 \sigma$ and $\pm 2 \sigma$ bands for a model with $m_{\phi} = 400 ~\mathrm{GeV}$ and $m_{s} = 100 ~\mathrm{GeV}$.

The observed limits, expected limits and $\pm 1 \sigma$ and $\pm 2 \sigma$ bands for a model with $m_{\phi} = 600 ~\mathrm{GeV}$ and $m_{s} = 50 ~\mathrm{GeV}$.

The observed limits, expected limits and $\pm 1 \sigma$ and $\pm 2 \sigma$ bands for a model with $m_{\phi} = 1000 ~\mathrm{GeV}$ and $m_{s} = 50 ~\mathrm{GeV}$.

The observed limits, expected limits and $\pm 1 \sigma$ and $\pm 2 \sigma$ bands for a model with $m_{\phi} = 1000 ~\mathrm{GeV}$ and $m_{s} = 150 ~\mathrm{GeV}$.

The observed limits, expected limits and $\pm 1 \sigma$ and $\pm 2 \sigma$ bands for a model with $m_{\phi} = 1000 ~\mathrm{GeV}$ and $m_{s} = 400 ~\mathrm{GeV}$.

Combined limits for the CalRatio and MS analyses, for a model with $m_{\phi} = 125 ~\mathrm{GeV}$ and $m_{s} = 5 ~\mathrm{GeV}$.

Combined limits for the CalRatio and MS analyses, for a model with $m_{\phi} = 125 ~\mathrm{GeV}$ and $m_{s} = 8 ~\mathrm{GeV}$.

Combined limits for the CalRatio and MS analyses, for a model with $m_{\phi} = 125 ~\mathrm{GeV}$ and $m_{s} = 15 ~\mathrm{GeV}$.

Combined limits for the CalRatio and MS analyses, for a model with $m_{\phi} = 125 ~\mathrm{GeV}$ and $m_{s} = 40 ~\mathrm{GeV}$.

Combined limits for the CalRatio and MS analyses, for a model with $m_{\phi} = 200 ~\mathrm{GeV}$ and $m_{s} = 8 ~\mathrm{GeV}$.

Combined limits for the CalRatio and MS analyses, for a model with $m_{\phi} = 200 ~\mathrm{GeV}$ and $m_{s} = 25 ~\mathrm{GeV}$.

Combined limits for the CalRatio and MS analyses, for a model with $m_{\phi} = 200 ~\mathrm{GeV}$ and $m_{s} = 50 ~\mathrm{GeV}$.

Combined limits for the CalRatio and MS analyses, for a model with $m_{\phi} = 400 ~\mathrm{GeV}$ and $m_{s} = 50 ~\mathrm{GeV}$.

Combined limits for the CalRatio and MS analyses, for a model with $m_{\phi} = 400 ~\mathrm{GeV}$ and $m_{s} = 100 ~\mathrm{GeV}$.

Combined limits for the CalRatio and MS analyses, for a model with $m_{\phi} = 600 ~\mathrm{GeV}$ and $m_{s} = 50 ~\mathrm{GeV}$.

Combined limits for the CalRatio and MS analyses, for a model with $m_{\phi} = 1000 ~\mathrm{GeV}$ and $m_{s} = 50 ~\mathrm{GeV}$.

Combined limits for the CalRatio and MS analyses, for a model with $m_{\phi} = 1000 ~\mathrm{GeV}$ and $m_{s} = 150 ~\mathrm{GeV}$.

Combined limits for the CalRatio and MS analyses, for a model with $m_{\phi} = 1000 ~\mathrm{GeV}$ and $m_{s} = 400 ~\mathrm{GeV}$.

Expected and observed events in the 16 discovery regions along with the according control regions.

Expected signal yield and acceptance x efficiency, estimated background and observed number of events in data for the full range of simulated masses in the MS-agnostic R-hadron search.

Expected signal yield and acceptance x efficiency, estimated background and observed number of events in data for the full range of simulated masses in the full-detector R-hadron search.

p0-values and model-independent upper limits on cross-section x acceptance x efficiency for the 16 discovery regions.

Expected signal yield and acceptance x efficiency, estimated background and observed number of events in data for the full range of simulated masses in the MS-agnostic search for metastable gluino R-hadrons.

Expected signal yield and acceptance x efficiency, estimated background and observed number of events in data for the full range of simulated masses in the full-detector direct-stau search.

Expected signal yield and acceptance x efficiency, estimated background and observed number of events in data for the full range of simulated masses in the full-detector chargino search.

Upper cross-section limit in gluino R-hadron search.

Upper cross-section limit in sbottom R-hadron search.

Upper cross-section limit in stop R-hadron search.

Upper cross-section limit in stau search.

Upper cross-section limit in chargino search.

Lower mass limit as function of gluino lifetime.

Acceptance x efficiency, acceptance and efficiency for the full range of simulated masses in the MS-agnostic R-hadron search.

Upper cross-section limit in meta-stable gluino R-hadron search.

Flavor composition of 800 GeV stop R-hadrons simulated using the generic model as a function of radial distance from the interaction point.

Flavor composition of 800 GeV anti-stop R-hadrons simulated using the generic model as a function of radial distance from the interaction point.

Flavor composition of 800 GeV stop R-hadrons simulated using the Regge model as a function of radial distance from the interaction point.

Flavor composition of 800 GeV anti-stop R-hadrons simulated using the Regge model as a function of radial distance from the interaction point.

ETmiss trigger efficiency as function of true ETmiss (EtmissTurnOn).

Single-muon trigger efficiency as function of $|\eta|$ and $\beta$ (SingleMuTurnOn).

Candidate reconstruction efficiency for ID+Calo selection (IDCaloEff).

Candidate reconstruction efficiency for loose selection (LooseEff).

Efficiency for a loose candidate to be promoted to a tight candidate (TightPromotionEff).

Resolution and average of reconstructed dE/dx mass for a given simulated mass for ID+calo candidates.

Resolution and average of reconstructed ToF mass for a given simulated mass for ID+calo candidates.

Resolution and average of reconstructed ToF mass for a given simulated mass for FullDet candidates.

Differential cross-section and uncertainty from each source, as a function of leading $p_{T}^j$ for the dominant process in the $e\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of leading $p_{T}^j$ for the dominant process in the extreme $eejj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of leading $p_{T}^j$ for the dominant process in the extreme $\mu\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of leading $p_{T}^j$ for the dominant process in the extreme $e\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of subleading $p_{T}^j$ for the dominant process in the $eejj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of subleading $p_{T}^j$ for the dominant process in the $\mu\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of subleading $p_{T}^j$ for the dominant process in the $e\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of subleading $p_{T}^j$ for the dominant process in the extreme $eejj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of subleading $p_{T}^j$ for the dominant process in the extreme $\mu\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of subleading $p_{T}^j$ for the dominant process in the extreme $e\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $min\Delta\phi(j_0,l)$ for the dominant process in the $eejj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $min\Delta\phi(j_0,l)$ for the dominant process in the $\mu\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $min\Delta\phi(j_0,l)$ for the dominant process in the $e\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $min\Delta\phi(j_0,l)$ for the dominant process in the extreme $eejj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $min\Delta\phi(j_0,l)$ for the dominant process in the extreme $\mu\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $min\Delta\phi(j_0,l)$ for the dominant process in the extreme $e\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $min\Delta\phi(j_1,l)$ for the dominant process in the $eejj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $min\Delta\phi(j_1,l)$ for the dominant process in the $\mu\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $min\Delta\phi(j_1,l)$ for the dominant process in the $e\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $min\Delta\phi(j_1,l)$ for the dominant process in the extreme $eejj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $min\Delta\phi(j_1,l)$ for the dominant process in the extreme $\mu\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $min\Delta\phi(j_1,l)$ for the dominant process in the extreme $e\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $\Delta\eta_{jj}$ for the dominant process in the $eejj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $\Delta\eta_{jj}$ for the dominant process in the $\mu\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $\Delta\eta_{jj}$ for the dominant process in the $e\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $\Delta\eta_{jj}$ for the dominant process in the extreme $eejj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $\Delta\eta_{jj}$ for the dominant process in the extreme $\mu\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $\Delta\eta_{jj}$ for the dominant process in the extreme $e\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $\Delta\phi_{jj}$ for the dominant process in the $eejj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $\Delta\phi_{jj}$ for the dominant process in the $\mu\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $\Delta\phi_{jj}$ for the dominant process in the $e\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $\Delta\phi_{jj}$ for the dominant process in the extreme $eejj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $\Delta\phi_{jj}$ for the dominant process in the extreme $\mu\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $\Delta\phi_{jj}$ for the dominant process in the extreme $e\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $\Delta\phi_{ll}$ for the dominant process in the $eejj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $\Delta\phi_{ll}$ for the dominant process in the $\mu\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $\Delta\phi_{ll}$ for the dominant process in the $e\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $\Delta\phi_{ll}$ for the dominant process in the extreme $eejj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $\Delta\phi_{ll}$ for the dominant process in the extreme $\mu\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $\Delta\phi_{ll}$ for the dominant process in the extreme $e\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $m_{jj}$ for the dominant process in the $eejj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $m_{jj}$ for the dominant process in the $\mu\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $m_{jj}$ for the dominant process in the $e\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $m_{jj}$ for the dominant process in the extreme $eejj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $m_{jj}$ for the dominant process in the extreme $\mu\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $m_{jj}$ for the dominant process in the extreme $e\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $p_{T}^{ee}$ for the dominant process in the $eejj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $p_{T}^{\mu\mu}$ for the dominant process in the $\mu\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $p_{T}^{e\mu}$ for the dominant process in the $e\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $p_{T}^{ee}$ for the dominant process in the extreme $eejj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $p_{T}^{\mu\mu}$ for the dominant process in the extreme $\mu\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $p_{T}^{e\mu}$ for the dominant process in the extreme $e\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $H_{T}$ for the dominant process in the $eejj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $H_{T}$ for the dominant process in the $\mu\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $H_{T}$ for the dominant process in the $e\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $H_{T}$ for the dominant process in the extreme $eejj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $H_{T}$ for the dominant process in the extreme $\mu\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $H_{T}$ for the dominant process in the extreme $e\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $S_{T}$ for the dominant process in the $ee jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $S_{T}$ for the dominant process in the $\mu\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $S_{T}$ for the dominant process in the $e\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $S_{T}$ for the dominant process in the extreme $eejj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $S_{T}$ for the dominant process in the extreme $\mu\mu jj$ measurement region.

Differential cross-section and uncertainty from each source, as a function of $S_{T}$ for the dominant process in the extreme $e\mu jj$ measurement region.

Expected and observed 95% CL lower limits on first- and second-generation leptoquark masses for different values of $\beta$.

Event yields in the dimuon channel control regions with total uncertainties. The observed number of events is given in the first row. The background event numbers as obtained from the fit are shown together with the total uncertainties. The second row shows the total background expectation, the further rows show the breakdown into different background components.

Event yields in the dielectron channel control regions with total uncertainties. The observed number of events is given in the first row. The background event numbers as obtained from the fit are shown together with the total uncertainties. The second row shows the total background expectation, the further rows show the breakdown into different background components.

Distribution of $m_{LQ}^{min}$ in the training region for the BDT for the $ee jj$ and $\mu\mu jj$ channels. Data are shown together with predicted total background expectation.

Distribution of $m_{LQ}^{T}$ in the training region for the BDT for the $e\nu jj$ and $\mu\nu jj$ channels. Data are shown together with predicted total background expectation.

Dijet mass distribution for the b-tagged category. Data, estimated background and uncertainties are shown. Events are collected using the combined trigger and contain a $E_T^{\gamma} > 95$ GeV photon and two $p_T^{jet} > 65$ GeV jets.

Upper limits on Gaussian-shape contributions to the dijet mass distributions from the flavour-inclusive category and masses below 450 GeV, for which the single-photon trigger was used.

Upper limits on Gaussian-shape contributions to the dijet mass distributions from the flavour-inclusive category and masses above 450 GeV, for which the combined trigger was used.

Upper limits on Gaussian-shape contributions to the dijet mass distributions from the b-tagged category and masses below 450 GeV, for which the single-photon trigger was used.

Upper limits on Gaussian-shape contributions to the dijet mass distributions from the b-tagged category and masses above 450 GeV, for which the combined trigger was used.

Kinematic acceptance values predicted for the $Z'$ model as a function of mass $m_{Z'}$ for the flavour-inclusive category using the single-photon trigger.

Kinematic acceptance values predicted for the $Z'$ model as a function of mass $m_{Z'}$ for the flavour-inclusive category using the combined trigger.

Kinematic acceptance values predicted for the $Z'$ model as a function of mass $m_{Z'}$ for the b-tagged category using the single-photon trigger.

Kinematic acceptance values predicted for the $Z'$ model as a function of mass $m_{Z'}$ for the b-tagged category using the combined trigger.

Reconstruction efficiency for $Z'$ model, flavour inclusive category, single-photon trigger.

Reconstruction efficiency for $Z'$ model, flavour inclusive category, combined trigger.

Reconstruction efficiency for $Z'$ model, b-tagged category, single-photon trigger.

Reconstruction efficiency for $Z'$ model, b-tagged category, combined trigger.

Ratio of unfolded width of azimuthal angular correlation distributions (P PB/ P P). Different colors correspond to different combinations of p_{T,1} and p_{T,2}

Ratio of unfolded Dijet conditional yields (P PB/ P P). Different colors correspond to different combinations of p_{T,1} and p_{T,2}

Unfolded width of azimuthal angular correlation distributions (Delta p_{T} > 3). Full markers represent p+Pb, open markers p+p

Unfolded Dijet conditional yields (Delta p_{T} > 3). Full markers represent p+Pb, open markers p+p

Ratio of unfolded width of azimuthal angular correlation distributions (P PB/ P P) (Delta p_{T} > 3). Different colors correspond to different combinations of p_{T,1} and p_{T,2}

Ratio of unfolded Dijet conditional yields (P PB/ P P) (Delta p_{T} > 3). Different colors correspond to different combinations of p_{T,1} and p_{T,2}

Unfolded azimuthal angular correlation distributions. Black markers represent p+Pb, red markers p+p

Unfolded azimuthal angular correlation distributions (Delta p_{T} > 3). Black markers represent p+Pb, red markers p+p

Predicted ratio of cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $0.6<|\eta^{\gamma}|<1.37$.

Measured ratio of cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $1.56<|\eta^{\gamma}|<1.81$.

Predicted ratio of cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $1.56<|\eta^{\gamma}|<1.81$.

Measured ratio of cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $1.81<|\eta^{\gamma}|<2.37$.

Predicted ratio of cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $1.81<|\eta^{\gamma}|<2.37$.

Measured double ratio of cross sections for inclusive isolated-photon production and Z-boson production as a function of $E_{\rm T}^{\gamma}$ for $|\eta^{\gamma}|<0.6$.

Predicted double ratio of cross sections for inclusive isolated-photon production and Z-boson production as a function of $E_{\rm T}^{\gamma}$ for $|\eta^{\gamma}|<0.6$.

Measured double ratio of cross sections for inclusive isolated-photon production and Z-boson production as a function of $E_{\rm T}^{\gamma}$ for $0.6<|\eta^{\gamma}|<1.37$.

Predicted double ratio of cross sections for inclusive isolated-photon production and Z-boson production as a function of $E_{\rm T}^{\gamma}$ for $0.6<|\eta^{\gamma}|<1.37$.

Measured double ratio of cross sections for inclusive isolated-photon production and Z-boson production as a function of $E_{\rm T}^{\gamma}$ for $1.56<|\eta^{\gamma}|<1.81$.

Predicted double ratio of cross sections for inclusive isolated-photon production and Z-boson production as a function of $E_{\rm T}^{\gamma}$ for $1.56<|\eta^{\gamma}|<1.81$.

Measured double ratio of cross sections for inclusive isolated-photon production and Z-boson production as a function of $E_{\rm T}^{\gamma}$ for $1.81<|\eta^{\gamma}|<2.37$.

Predicted double ratio of cross sections for inclusive isolated-photon production and Z-boson production as a function of $E_{\rm T}^{\gamma}$ for $1.81<|\eta^{\gamma}|<2.37$.

Unfolded charm and bottom hadron yields in bins of transverse momentum.

Fraction of bottom electrons obtained with the unfolding procedure (red), compared to a pQCD FONLL calculation (gray), with uncertainties arising from the quark masses and regularization scales.