Electron $p_{T}$ distribution using 2016-2018 data sets. The complete set of selection criteria were applied. Two examples of SSM WPRIME boson signal samples with masses of 3.8 and 5.6 TeV are shown. The lower panel shows the ratio of data to SM prediction, and the shaded band represents the systematic uncertainties.

$p_{T}^{miss}$ distribution in the electron channel using 2016-2018 data sets. The complete set of selection criteria were applied. Two examples of SSM WPRIME boson signal samples with masses of 3.8 and 5.6 TeV are shown. The lower panel shows the ratio of data to SM prediction, and the shaded band represents the systematic uncertainties.

Muon $p_T$ distribution using 2016-2018 data sets. The complete set of selection criteria were applied. Two examples of SSM WPRIME boson signal samples with masses of 3.8 and 5.6 TeV are shown. The lower panel shows the ratio of data to SM prediction, and the shaded band represents the systematic uncertainties.

$p_T^{miss}$ distribution in the muon channel using 2016-2018 data sets. The complete set of selection criteria were applied. Two examples of SSM WPRIME boson signal samples with masses of 3.8 and 5.6 TeV are shown. The lower panel shows the ratio of data to SM prediction, and the shaded band represents the systematic uncertainties.

$M_T$ distribution for the E+INVISIBLE system using 2016-2018 data sets. The complete set of selection criteria were applied. Two examples of SSM WPRIME boson signal samples with masses of 3.8 and 5.6 TeV are shown. The lower panel shows the ratio of data to SM prediction, and the shaded band represents the systematic uncertainties.

$M_T$ distribution for the MU+INVISIBLE system using 2016-2018 data sets. The complete set of selection criteria were applied. Two examples of SSM WPRIME boson signal samples with masses of 3.8 and 5.6 TeV are shown. The lower panel shows the ratio of data to SM prediction, and the shaded band represents the systematic uncertainties.

Theoretical prediction for the production and decay cross-section of SSM WPRIME bosons (W --> LEPTON + NU) as a function of the WPRIME mass, for the range 200-6400 GeV and inclusive in phase-space (no cuts). The uncertainty shown covers PDF and ALPHAS uncertainties. These theoretical predictions are obtained with PYTHIA (LO) and corrected to NNLO in QCD using FEWZ program.

Observed (solid line) and expected (dashed line) upper limits at 95% CL on the product of WPRIME cross-section production and BF(WPRIME --> LEPTON + NU) for an SSM WPRIME boson, as a function of the boson mass, for the electron decay channel. The shaded bands represent the one (green) and two (yellow) standard deviation uncertainty bands for the expected limits. The theoretical predictions for the SSM at NNLO precision in QCD are shown with narrow gray bands corresponding to the PDF and ALPHAS uncertainties.

Observed (solid line) and expected (dashed line) upper limits at 95% CL on the product of WPRIME cross-section production and BF(WPRIME --> LEPTON + NU) for an SSM WPRIME boson, as a function of the boson mass, for the muon decay channel. The shaded bands represent the one (green) and two (yellow) standard deviation uncertainty bands for the expected limits. The theoretical predictions for the SSM at NNLO precision in QCD are shown with narrow gray bands corresponding to the PDF and ALPHAS uncertainties.

Observed (solid line) and expected (dashed line) upper limits at 95% CL on the product of WPRIME cross-section production and BF(WPRIME --> LEPTON + NU) for an SSM WPRIME boson, as a function of the boson mass, for the combined electron and muon decay channels. The shaded bands represent the one (green) and two (yellow) standard deviation uncertainty bands for the expected limits. The theoretical predictions for the SSM at NNLO precision in QCD are shown with narrow gray bands corresponding to the PDF and ALPHAS uncertainties.

The 95% CL observed (solid line) and expected (dashed line) model independent cross section upper limits as function of the $MT_{min}$ threshold, for the electron decay channel. The shaded bands represent the one (green) and two (yellow) standard deviation uncertainty bands for the expected limits.

The 95% CL observed (solid line) and expected (dashed line) model independent cross section upper limits as function of the $MT_{min}$ threshold, for the muon decay channel. The shaded bands represent the one (green) and two (yellow) standard deviation uncertainty bands for the expected limits.

The 95% CL observed (solid line) and expected (dashed line) model independent cross section upper limits as function of the $MT_{min}$ threshold, for the combined electron and muon decay channels. The shaded bands represent the one (green) and two (yellow) standard deviation uncertainty bands for the expected limits.

Observed (solid line) and expected (dashed line) upper limits at 95% CL on the coupling strength ratio, gWprime/gW as a function of the mass of the WPRIME boson, for the electron channel. The one (green) and two (yellow) standard deviation uncertainty bands for the expected limits are shown. The area above the limit curve is excluded. The dotted line represents the case of SSM coupling, gWprime, being equal to gW, the SM coupling.

Observed (solid line) and expected (dashed line) upper limits at 95% CL on the coupling strength ratio, gWprime/gW, as a function of the mass of the WPRIME boson, for the muon channel. The one (green) and two (yellow) standard deviation uncertainty bands for the expected limits are shown. The area above the limit curve is excluded. The dotted line represents the case of SSM coupling, gWprime , being equal to gW, the SM coupling.

Exclusion limits in the 2D plane (1/R, $\mu$) for the split-UED interpretation for the n = 2 case, for the electron channel for the 2016-2018 data sets. R is the radius of the additional spatial dimension and $\mu$ the bulk mass for the fermion field in five dimensions. The expected limit is depicted as a black dashed line. The one (green) and two (yellow) standard deviation uncertainty bands for the expected limits are shown. The experimentally excluded region is the entire area to the left of the solid black line.

Exclusion limits in the 2D plane (1/R, $\mu$) for the split-UED interpretation for the n = 2 case, for the muon channel for the 2016-2018 data sets. R is the radius of the additional spatial dimension and $\mu$ the bulk mass for the fermion field in five dimensions. The expected limit is depicted as a black dashed line. The one (green) and two (yellow) standard deviation uncertainty bands for the expected limits are shown. The experimentally excluded region is the entire area to the left of the solid black line.

Exclusion limits in the 2D plane (1/R, $\mu$) for the split-UED interpretation for the n = 2 case, for the combined electron and muon channels for the 2016-2018 data sets. R is the radius of the additional spatial dimension and $\mu$ the bulk mass for the fermion field in five dimensions. The expected limit is depicted as a black dashed line. The one (green) and two (yellow) standard deviation uncertainty bands for the expected limits are shown. The experimentally excluded region is the entire area to the left of the solid black line.

Observed (solid line) and expected (dashed line) upper limits at 95% CL on the ${\lambda}_{231}$ coupling in the RPV SUSY model with a STAU mediator, as a function of the mass of STAU, for the electron channel and for the production coupling, ${\lambda}^{'}_{3ij}$=0.5 . The couplings ${\lambda}^{'}_{3ij}$, ${\lambda}_{231}$, and ${\lambda}_{132}$ are defined in Fig. 1. The one (green) and two (yellow) standard deviation uncertainty bands for the expected limits are shown. The area above the limit curve is excluded. Limits for other values of ${\lambda}^{'}_{3ij}$ are obtained multiplying the ones shown by the ratio ${\lambda}^{'}_{3ij}$/0.5

Observed (solid line) and expected (dashed line) upper limits at 95% CL on the ${\lambda}_{132}$ coupling in the RPV SUSY model with a stau mediator, as a function of the mass of the stau, for the muon channel and for the production coupling, ${\lambda}^{'}_{3ij}$ = 0.5 . The couplings ${\lambda}^{'}_{3ij}$, ${\lambda}_{231}$, and ${\lambda}_{132}$ are defined in Fig. 1. The one (green) and two (yellow) standard deviation uncertainty bands for the expected limits are shown. The area above the limit curve is excluded. Limits for other values of ${\lambda}^{'}_{3ij}$ are obtained multiplying these ones by the ratio ${\lambda}^{'}_{3ij}$/0.5

Region in the oblique (W,Y) parameter phase space allowed by the current analysis at 95% CL. The combination of the electron and muon channel distributions from the 2017 and 2018 data sets at sqrt(s) = 13 TeV is used, having 101 fb-1 of luminosity.

Negative Log-Likelihood for the determination of the oblique W parameter, for the combination of the electron and muon channel and for 2017 and 2018 data sets (L=101 fb-1) at sqrt(s) = 13 TeV.

Total background estimate and observed data in all bins used in the limit calculation for the SSM WPRIME limits. The total event sample is split into the three years of data taking and the two lepton flavors.The distributions being shown are $M_T$ ones. The associated integrated luminosities for each year are of 35.9, 41.5, and 59.4 fb$̣^{-1}. The mass bins are numbered in ascending order.

Bayesian upper exclusion limits on the ratio $g_{W'}/g_{W}$ for an SSM-like W$\prime$ boson are shown. The unity coupling ratio (blue dotted curve) corresponds to the SSM common benchmark. The 68 and 95% quantiles of the limits are represented by the green and yellow bands, respectively.

Bayesian lower exclusion limits on the NUGIM G(221) mixing angle $\cot(\theta_{E})$ are shown as a function of the W$\prime$ boson mass. The theoretically excluded region is shaded in grey. The 68 and 95% quantiles of the limits are represented by the green and yellow bands, respectively.

Bayesian upper exclusion limits at 95% CL on the product of the production cross section and branching fraction of a QBH in an associated $ au$ lepton and neutrino final state. Minimum threshold masses $m_{th}$ of up to 6.6 TeV are excluded at 95% CL. The observed limit (solid line) is obtained from the intersection with the LO QBH cross section (blue dotted curve). The 68 and 95% quantiles of the limits are represented by the green and yellow bands, respectively.

Bayesian upper limits at 95% CL on the cross section of the process $pp\rightarrow\tau\nu$ mediated via LQ exchange in the t-channel. The inner (green) band and the outer (yellow) band indicate the regions containing 68 and 95%, respectively, of the distribution of limits expected under the background-only hypothesis. The predicted LQ cross section at LO in the three coupling benchmark scenarios is depicted in different colors for $g_{U}=1$. The uncertainty bandy correspond to the sum in quadrature of PDF and scale variations. The first benchmark scenario considers only couplings to left-handed SM fermions (i.e. $\beta_{\text{R}}^{ij}=0$) and is referred to as "best fit LH". The second benchmark, referred to as "best fit LH+RH", considers $|\beta_{\text{R}}^{\text{b}\tau}|=1$ and all other $\beta_{\text{R}}^{ij}=0$. In the third "democratic" benchmark, equal couplings only to LH fermions are assumed, i.e. $\beta_{\text{L}}^{ij}=1$ and $\beta_{\text{R}}^{ij}=0$ for all $i$ and $j$.

Expected and observed lower limits of the LQ mass as a function of the coupling $g_{U}$ in the LH scenario. The blue band shows the 68% and 95% regions of $g_{U}$ preferred by the fit to the b anomalies data.

Expected and observed lower limits of the LQ mass as a function of the coupling $g_{U}$ in the LH+RH scenario. The blue band shows the 68% and 95% regions of $g_{U}$ preferred by the fit to the b anomalies data.

Expected and observed lower limits of the LQ mass as a function of the coupling $g_{U}$ in the democratic scenario. The blue band shows the 68% and 95% regions of $g_{U}$ preferred by the fit to the b anomalies data.

Bayesian upper exclusion limits at 95% CL on each of the Wilson coefficients described by the EFT model based on 2016-2018 data. The three different coupling types represent a left-handed vector coupling ($\epsilon^{cb}_{L}$), tensor-like coupling ($\epsilon^{cb}_{T}$), and scalar-tensor-like coupling ($\epsilon^{cb}_{S_{L}}$). The 68 and 95% quantiles of the limits are represented by the green and yellow bands, respectively.

Summary of exclusion limits (expected and observed) calculated at 95% CL for full Run-2 CMS data.

Background prediction and observed data yields in the signal region bins. The background yields are obtained from the background-only fit and serve as input to the simplified likelihood reinterpretation scheme. The naming of the bins is "year_binnumber", following the binning from Figure 4.

Matrix of covariance coefficients between signal region bins. The coefficients are obtained from the background-only fit and serve as input to the simplified likelihood reinterpretation scheme. The naming of the bins is "year_binnumber", following the binning used in Figure 4.

Predicted signal yields for the 2017 data-taking period, corresponding to 41.3 fb$^{-1}$, after the application of each search requirement (cumulative) for various signal hypothesis. The requirements listed are presented as total efficiencies w.r.t. the previous selection step.

Measured differential cross section as a function of observable $ p_{T}^{ll} - p_{T}^{\gamma}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{ll} + p_{T}^{\gamma}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{ll} + p_{T}^{\gamma}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ \Delta R (l,l)$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ \Delta R (l,l)$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ N_{jets}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ N_{jets}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{Jet1}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{Jet1}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{Jet2}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{Jet2}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{Jet2}/p_{T}^{Jet1}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{Jet2}/p_{T}^{Jet1}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ m_{jj}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ m_{jj}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ m_{ll\gamma j}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ m_{ll\gamma j}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ H_{T}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ H_{T}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{\gamma} / \sqrt{H_{T}}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{\gamma} / \sqrt{H_{T}}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ \Delta \phi (Jet,\gamma)$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ \Delta \phi (Jet,\gamma)$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{ll\gamma j}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{ll\gamma j}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ \phi_{CS}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ \phi_{CS}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ \cos \theta_{CS}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ \cos \theta_{CS}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{ll\gamma} / m_{ll\gamma}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{ll\gamma} / m_{ll\gamma}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{ll\gamma} / m_{ll\gamma}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{ll\gamma} / m_{ll\gamma}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{ll\gamma} / m_{ll\gamma}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{ll\gamma} / m_{ll\gamma}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{ll} - p_{T}^{\gamma}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{ll} - p_{T}^{\gamma}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{ll} - p_{T}^{\gamma}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{ll} - p_{T}^{\gamma}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{ll} - p_{T}^{\gamma}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{ll} - p_{T}^{\gamma}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{ll\gamma j}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{ll\gamma j}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{ll\gamma j}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{ll\gamma j}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{ll\gamma j}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{ll\gamma j}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{\gamma} / \sqrt{H_{T}}$ (Fig. 8 (b))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{\gamma} / \sqrt{H_{T}}$ (Fig. 8 (b))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ H_{T}$ (Fig. 8 (a))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ H_{T}$ (Fig. 8 (a))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ \Delta \phi (Jet,\gamma)$ (Fig. 8 (c))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ \Delta \phi (Jet,\gamma)$ (Fig. 8 (c))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ \Delta R (l,l)$ (Fig. 5 (d))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ \Delta R (l,l)$ (Fig. 5 (d))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{ll} - p_{T}^{\gamma}$ (Fig. 5 (b))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{ll} - p_{T}^{\gamma}$ (Fig. 5 (b))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{ll} - p_{T}^{\gamma} \textrm{ in bin } p_{T}^{ll} + p_{T}^{\gamma} < 200 GeV$ (Fig. 11 (a))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{ll} - p_{T}^{\gamma} \textrm{ in bin } p_{T}^{ll} + p_{T}^{\gamma} < 200 GeV$ (Fig. 11 (a))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{ll} - p_{T}^{\gamma} \textrm{ in bin } 200 GeV < p_{T}^{ll} + p_{T}^{\gamma} < 300 GeV$ (Fig. 11 (b))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{ll} - p_{T}^{\gamma} \textrm{ in bin } 200 GeV < p_{T}^{ll} + p_{T}^{\gamma} < 300 GeV$ (Fig. 11 (b))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{ll} - p_{T}^{\gamma} \textrm{ in bin } p_{T}^{ll} + p_{T}^{\gamma} > 300 GeV$ (Fig. 11 (c))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{ll} - p_{T}^{\gamma} \textrm{ in bin } p_{T}^{ll} + p_{T}^{\gamma} > 300 GeV$ (Fig. 11 (c))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ m_{jj}$ (Fig. 7 (a))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ m_{jj}$ (Fig. 7 (a))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ m_{ll\gamma j}$ (Fig. 7 (b))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ m_{ll\gamma j}$ (Fig. 7 (b))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ N_{jets}$ (Fig. 6 (a))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ N_{jets}$ (Fig. 6 (a))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{Jet1}$ (Fig. 6 (b))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{Jet1}$ (Fig. 6 (b))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{Jet2}$ (Fig. 6 (c))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{Jet2}$ (Fig. 6 (c))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{Jet2}/p_{T}^{Jet1}$ (Fig. 6 (d))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{Jet2}/p_{T}^{Jet1}$ (Fig. 6 (d))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{ll}$ (Fig. 5 (a))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{ll}$ (Fig. 5 (a))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{ll\gamma j}$ (Fig. 8 (d))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{ll\gamma j}$ (Fig. 8 (d))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{ll\gamma j} \textrm{ in bin } p_{T}^{ll\gamma} < 50 GeV$ (Fig. 12 (a))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{ll\gamma j} \textrm{ in bin } p_{T}^{ll\gamma} < 50 GeV$ (Fig. 12 (a))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{ll\gamma j} \textrm{ in bin } 50 GeV < p_{T}^{ll\gamma} < 75 GeV$ (Fig. 12 (b))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{ll\gamma j} \textrm{ in bin } 50 GeV < p_{T}^{ll\gamma} < 75 GeV$ (Fig. 12 (b))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{ll\gamma j} \textrm{ in bin } p_{T}^{ll\gamma} > 75 GeV$ (Fig. 12 (c))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{ll\gamma j} \textrm{ in bin } p_{T}^{ll\gamma} > 75 GeV$ (Fig. 12 (c))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{ll\gamma} / m_{ll\gamma} \textrm{ in bin } 125 GeV < m_{ll\gamma} < 200 GeV$ (Fig. 10 (a))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{ll\gamma} / m_{ll\gamma} \textrm{ in bin } 125 GeV < m_{ll\gamma} < 200 GeV$ (Fig. 10 (a))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{ll\gamma} / m_{ll\gamma} \textrm{ in bin } 200 GeV < m_{ll\gamma} < 300 GeV$ (Fig. 10 (b))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{ll\gamma} / m_{ll\gamma} \textrm{ in bin } 200 GeV < m_{ll\gamma} < 300 GeV$ (Fig. 10 (b))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{ll\gamma} / m_{ll\gamma} \textrm{ in bin } m_{ll\gamma} > 300 GeV$ (Fig. 10 (c))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{ll\gamma} / m_{ll\gamma} \textrm{ in bin } m_{ll\gamma} > 300 GeV$ (Fig. 10 (c))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{ll} + p_{T}^{\gamma}$ (Fig. 5 (c))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{ll} + p_{T}^{\gamma}$ (Fig. 5 (c))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ \cos \theta_{CS}$ (Fig. 9 (b))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ \cos \theta_{CS}$ (Fig. 9 (b))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ \phi_{CS}$ (Fig. 9 (a))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ \phi_{CS}$ (Fig. 9 (a))

Best fit of the cross section.

Expected and observed upper limits on the AQGC operators $a^Z_C/\Lambda^2$, with no unitarization. The $y$ axis shows the limit on the ratio of the observed cross section to the cross section predicted for each anomalous coupling value ($\sigma_\mathrm{AQGC}$).

Limits on LEP-like dimension-6 anomalous quartic gauge coupling parameters, with and without unitarization via a clipping procedure.

Conversion of limits on $a^W_0$ to dimension-8 $f_{M,i}$ operators, using the assumption of vanishing $WWZ\gamma$ couplings to eliminate some parameters. When quoting limits on one of the operators, the other is fixed to zero. The results for $|f_{M,0}/\Lambda^{4}|$ and $|f_{M,4}/\Lambda^{4}|$ are shown with and without clipping of the signal model at 1.4 TeV, when the other parameter is fixed to the SM value of zero.

Conversion of limits on $a^W_0$ and $a^W_C$ to dimension-8 $f_{M,i}$ operators, using the assumption that all $f_{M,i}$ except one are equal to zero. The results are shown with and without clipping of the signal model at 1.4 TeV.

{Expected and observed limits in the two-dimensional plane of $a^W_0/\Lambda^2$ vs. $a^W_C/\Lambda^2$. The limits are described by analytical ellipses of equation $(x-x0)^2/a^2 + (y-y0)^2/b^2 = 1$ and rotated counter-clockwise by $\theta$ degrees, where $x$ and $y$ in the equation correspond to the $a_0^W$ and $a_C^W$ couplings, respectively.

{Expected and observed limits in the two-dimensional plane of $a^W_0/\Lambda^2$ vs. $a^W_C/\Lambda^2$ with unitarization imposed by clipping the signal model at 1.4 TeV. The limits are described by analytical ellipses of equation $(x-x0)^2/a^2 + (y-y0)^2/b^2 = 1$ and rotated counter-clockwise by $\theta$ degrees, where $x$ and $y$ in the equation correspond to the $a_0^W$ and $a_C^W$ couplings, respectively.

{Expected and observed limits in the two-dimensional plane of $a^Z_0/\Lambda^2$ vs. $a^Z_C/\Lambda^2$. The limits are described by analytical ellipses of equation $(x-x0)^2/a^2 + (y-y0)^2/b^2 = 1$ and rotated counter-clockwise by $\theta$ degrees, where $x$ and $y$ in the equation correspond to the $a_0^Z$ and $a_C^Z$ couplings, respectively.

Charged-hadron spectrum in the centrality interval 5-10% for p+Pb, divided by &#9001;TPPB&#9002;. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Charged-hadron spectrum in the centrality interval 10-20% for p+Pb, divided by &#9001;TPPB&#9002;. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Charged-hadron spectrum in the centrality interval 20-30% for p+Pb, divided by &#9001;TPPB&#9002;. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Charged-hadron spectrum in the centrality interval 30-40% for p+Pb, divided by &#9001;TPPB&#9002;. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Charged-hadron spectrum in the centrality interval 40-60% for p+Pb, divided by &#9001;TPPB&#9002;. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Charged-hadron spectrum in the centrality interval 60-90% for p+Pb, divided by &#9001;TPPB&#9002;. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Charged-hadron spectrum in the centrality interval 0-90% for p+Pb, divided by &#9001;TPPB&#9002;. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Charged-hadron cross-section in pp collisions. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Charged-hadron spectrum in the centrality interval 0-5% for Pb+Pb, divided by &#9001;TAA&#9002;. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature. The systematic uncertainty on momentum bias is negligible at low pT; in such cases, it is omitted in the table below.

Charged-hadron spectrum in the centrality interval 5-10% for Pb+Pb, divided by &#9001;TAA&#9002;. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature. The systematic uncertainty on momentum bias is negligible at low pT; in such cases, it is omitted in the table below.

Charged-hadron spectrum in the centrality interval 10-20% for Pb+Pb, divided by &#9001;TAA&#9002;. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature. The systematic uncertainty on momentum bias is negligible at low pT; in such cases, it is omitted in the table below.

Charged-hadron spectrum in the centrality interval 20-30% for Pb+Pb, divided by &#9001;TAA&#9002;. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature. The systematic uncertainty on momentum bias is negligible at low pT; in such cases, it is omitted in the table below.

Charged-hadron spectrum in the centrality interval 30-40% for Pb+Pb, divided by &#9001;TAA&#9002;. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature. The systematic uncertainty on momentum bias is negligible at low pT; in such cases, it is omitted in the table below.

Charged-hadron spectrum in the centrality interval 40-50% for Pb+Pb, divided by &#9001;TAA&#9002;. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature. The systematic uncertainty on momentum bias is negligible at low pT; in such cases, it is omitted in the table below.

Charged-hadron spectrum in the centrality interval 50-60% for Pb+Pb, divided by &#9001;TAA&#9002;. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature. The systematic uncertainty on momentum bias is negligible at low pT; in such cases, it is omitted in the table below.

Charged-hadron spectrum in the centrality interval 60-80% for Pb+Pb, divided by &#9001;TAA&#9002;. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature. The systematic uncertainty on momentum bias is negligible at low pT; in such cases, it is omitted in the table below.

Charged-hadron cross-section in pp collisions. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Charged-hadron spectrum in the centrality interval 0-5% for Xe+Xe, divided by &#9001;TAA&#9002;. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Charged-hadron spectrum in the centrality interval 5-10% for Xe+Xe, divided by &#9001;TAA&#9002;. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Charged-hadron spectrum in the centrality interval 10-20% for Xe+Xe, divided by &#9001;TAA&#9002;. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Charged-hadron spectrum in the centrality interval 20-30% for Xe+Xe, divided by &#9001;TAA&#9002;. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Charged-hadron spectrum in the centrality interval 30-40% for Xe+Xe, divided by &#9001;TAA&#9002;. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Charged-hadron spectrum in the centrality interval 40-50% for Xe+Xe, divided by &#9001;TAA&#9002;. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Charged-hadron spectrum in the centrality interval 50-60% for Xe+Xe, divided by &#9001;TAA&#9002;. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Charged-hadron spectrum in the centrality interval 60-80% for Xe+Xe, divided by &#9001;TAA&#9002;. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 0-5% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 5-10% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 10-20% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 20-30% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 30-40% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 40-60% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 60-90% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 0-90% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 0-5% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature. The systematic uncertainty on momentum bias is negligible at low pT; in such cases, it is omitted in the table below.

Nuclear modification factor in centrality interval 5-10% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature. The systematic uncertainty on momentum bias is negligible at low pT; in such cases, it is omitted in the table below.

Nuclear modification factor in centrality interval 10-20% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature. The systematic uncertainty on momentum bias is negligible at low pT; in such cases, it is omitted in the table below.

Nuclear modification factor in centrality interval 20-30% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature. The systematic uncertainty on momentum bias is negligible at low pT; in such cases, it is omitted in the table below.

Nuclear modification factor in centrality interval 30-40% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature. The systematic uncertainty on momentum bias is negligible at low pT; in such cases, it is omitted in the table below.

Nuclear modification factor in centrality interval 40-50% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature. The systematic uncertainty on momentum bias is negligible at low pT; in such cases, it is omitted in the table below.

Nuclear modification factor in centrality interval 50-60% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature. The systematic uncertainty on momentum bias is negligible at low pT; in such cases, it is omitted in the table below.

Nuclear modification factor in centrality interval 60-80% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature. The systematic uncertainty on momentum bias is negligible at low pT; in such cases, it is omitted in the table below.

Nuclear modification factor in centrality interval 0-5% for Xe+Xe. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 5-10% for Xe+Xe. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 10-20% for Xe+Xe. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 20-30% for Xe+Xe. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 30-40% for Xe+Xe. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 40-50% for Xe+Xe. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 50-60% for Xe+Xe. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 60-80% for Xe+Xe. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 0-5% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 0-5% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 0-5% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 0-5% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 5-10% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 5-10% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 5-10% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 5-10% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 10-20% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 10-20% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 10-20% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 10-20% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 20-30% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 20-30% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 20-30% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 20-30% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 30-40% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 30-40% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 30-40% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 30-40% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 40-60% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 40-60% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 40-60% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 40-60% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 60-90% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 60-90% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 60-90% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 60-90% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 0-90% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 0-90% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 0-90% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 0-90% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 0-5% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 0-5% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 0-5% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 0-5% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 5-10% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 5-10% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 5-10% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 5-10% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 10-20% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 10-20% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 10-20% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 10-20% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 20-30% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 20-30% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 20-30% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 20-30% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 30-40% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 30-40% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 30-40% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 30-40% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 40-50% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 40-50% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 40-50% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 40-50% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 50-60% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 50-60% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 50-60% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 50-60% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 60-80% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 60-80% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 60-80% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 60-80% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 0-5% for Xe+Xe. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 0-5% for Xe+Xe. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 0-5% for Xe+Xe. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 5-10% for Xe+Xe. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 5-10% for Xe+Xe. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 5-10% for Xe+Xe. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 10-20% for Xe+Xe. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 10-20% for Xe+Xe. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 10-20% for Xe+Xe. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 20-30% for Xe+Xe. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 20-30% for Xe+Xe. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 20-30% for Xe+Xe. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 30-40% for Xe+Xe. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 30-40% for Xe+Xe. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 30-40% for Xe+Xe. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 40-50% for Xe+Xe. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 40-50% for Xe+Xe. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 40-50% for Xe+Xe. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 50-60% for Xe+Xe. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 50-60% for Xe+Xe. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 50-60% for Xe+Xe. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 60-80% for Xe+Xe. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 60-80% for Xe+Xe. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

Nuclear modification factor in centrality interval 60-80% for Xe+Xe. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.

The values of $\langle \mathrm{d}N_\mathrm{ch} / \mathrm{d}\eta \rangle$ averaged over $|\eta|<0.5$ for the INEL, NSD, and INEL>0 event classes at $\sqrt{s} = 5.02$ TeV

Pseudorapidity density distributions of charged particles, $\mathrm{d}N_{\mathrm{ch}}/\mathrm{d}\eta$, in pp collisions at $\sqrt{s} = $ 5.02 TeV for the INEL>0 with momentum threshold $p_{T}>0.15 \mathrm{GeV}/c$ ($\mathrm{INEL>0}_{p_{\mathrm{T}}>0.15}^{|\eta|<0.8}$).

Pseudorapidity density distributions of charged particles, $\mathrm{d}N_{\mathrm{ch}}/\mathrm{d}\eta$, in pp collisions at $\sqrt{s} = $ 5.02 TeV for the INEL>0 with momentum threshold $p_{T}>0.5 \mathrm{GeV}/c$ ($\mathrm{INEL>0}_{p_{\mathrm{T}}>0.5}^{|\eta|<0.8}$).

Pseudorapidity density distributions of charged particles, $\mathrm{d}N_{\mathrm{ch}}/\mathrm{d}\eta$, in pp collisions at $\sqrt{s} = $ 5.02 TeV for the INEL>0 with momentum threshold $p_{T}>1 \mathrm{GeV}/c$ ($\mathrm{INEL>0}_{p_{\mathrm{T}}>1}^{|\eta|<0.8}$).

Pseudorapidity density distributions of charged particles, $\mathrm{d}N_{\mathrm{ch}}/\mathrm{d}\eta$, in pp collisions at $\sqrt{s} = $ 5.02 TeV for the INEL>0 with momentum threshold $p_{T}>2 \mathrm{GeV}/c$ ($\mathrm{INEL>0}_{p_{\mathrm{T}}>2}^{|\eta|<0.8}$).

Pseudorapidity density distributions of charged particles, $\mathrm{d}N_{\mathrm{ch}}/\mathrm{d}\eta$, in pp collisions at $\sqrt{s} = $ 13 TeV for the INEL>0 with momentum threshold $p_{T}>0.15 \mathrm{GeV}/c$ ($\mathrm{INEL>0}_{p_{\mathrm{T}}>0.15}^{|\eta|<0.8}$).

Pseudorapidity density distributions of charged particles, $\mathrm{d}N_{\mathrm{ch}}/\mathrm{d}\eta$, in pp collisions at $\sqrt{s} = $ 13 TeV for the INEL>0 with momentum threshold $p_{T}>0.5 \mathrm{GeV}/c$ ($\mathrm{INEL>0}_{p_{\mathrm{T}}>0.5}^{|\eta|<0.8}$).

Pseudorapidity density distributions of charged particles, $\mathrm{d}N_{\mathrm{ch}}/\mathrm{d}\eta$, in pp collisions at $\sqrt{s} = $ 13 TeV for the INEL>0 with momentum threshold $p_{T}>1 \mathrm{GeV}/c$ ($\mathrm{INEL>0}_{p_{\mathrm{T}}>1}^{|\eta|<0.8}$).

Pseudorapidity density distributions of charged particles, $\mathrm{d}N_{\mathrm{ch}}/\mathrm{d}\eta$, in pp collisions at $\sqrt{s} = $ 13 TeV for the INEL>0 with momentum threshold $p_{T}>2 \mathrm{GeV}/c$ ($\mathrm{INEL>0}_{p_{\mathrm{T}}>2}^{|\eta|<0.8}$).

Transverse momentum spectra for the jet region, obtained as toward-transverse. Events with a leading track with PT>5 GEV at midrapidity are selected. The spectrum is shown in Figure 1 (right panel).

Coalescence parameter B2 as a function of the transverse momentum per nucleon pT/A, in the underlying event (transverse region). Events with a leading track with PT>5 GEV at midrapidity are selected. The B2 is shown in Figure 2 (both panels).

Coalescence parameter B2 as a function of the transverse momentum per nucleon pT/A, in the jet (transverse-toward region). Events with a leading track with PT>5 GEV at midrapidity are selected. The B2 is shown in Figure 2 (both panels).

Fraction of non-prompt J/$\psi$ in p--Pb collisions at $\sqrt{s_\mathrm{NN}}$ = 8.16 TeV as a function of $p_\mathrm{T}$.

d$^2\sigma$/d$y$d$p_{\rm T}$ in bins of $p_{\mathrm{T}}^{J/\psi}$ for prompt J/$\psi$ in p--Pb collisions at $\sqrt{s_{NN}}$ = 8.16 TeV.

d$^2\sigma$/d$y$d$p_{\rm T}$ in bins of $p_{\mathrm{T}}^{J/\psi}$ for non-prompt J/$\psi$ in p--Pb collisions at $\sqrt{s_{NN}}$ = 8.16 TeV.

Nuclear modification factor ($R_{pPb}$) of prompt J/$\psi$ in p--Pb collisions at $\sqrt{s_{NN}}$ = 8.16 TeV at midrapidity.

Nuclear modification factor ($R_{pPb}$) of non-prompt J/$\psi$ in p--Pb collisions at $\sqrt{s_{NN}}$ = 8.16 TeV at midrapidity.

Antideuteron spectrum in 5-10% V0M centrality class

Deuteron spectrum in 10-20% V0M centrality class

Antideuteron spectrum in 10-20% V0M centrality class

Deuteron spectrum in 20-30% V0M centrality class

Antideuteron spectrum in 20-30% V0M centrality class

Deuteron spectrum in 30-40% V0M centrality class

Antideuteron spectrum in 30-40% V0M centrality class

Deuteron spectrum in 40-50% V0M centrality class

Antideuteron spectrum in 40-50% V0M centrality class

Deuteron spectrum in 50-60% V0M centrality class

Antideuteron spectrum in 50-60% V0M centrality class

Deuteron spectrum in 60-70% V0M centrality class

Antideuteron spectrum in 60-70% V0M centrality class

Deuteron spectrum in 70-80% V0M centrality class

Antideuteron spectrum in 70-80% V0M centrality class

Deuteron spectrum in 80-90% V0M centrality class

Antideuteron spectrum in 80-90% V0M centrality class

$^3$He spectrum in 0-5% V0M centrality class

Anti$^3$He spectrum in 0-5% V0M centrality class

$^3$He spectrum in 5-10% V0M centrality class

Anti$^3$He spectrum in 5-10% V0M centrality class

$^3$He spectrum in 10-30% V0M centrality class

Anti$^3$He spectrum in 10-30% V0M centrality class

$^3$He spectrum in 30-50% V0M centrality class

Anti$^3$He spectrum in 30-50% V0M centrality class

$^3$He spectrum in 50-90% V0M centrality class

Anti$^3$He spectrum in 50-90% V0M centrality class

Triton spectrum in 0-10% V0M centrality class

Antitriton spectrum in 0-10% V0M centrality class

Triton spectrum in 10-30% V0M centrality class

Antitriton spectrum in 10-30% V0M centrality class

Triton spectrum in 30-50% V0M centrality class

Antitriton spectrum in 30-50% V0M centrality class

Triton spectrum in 50-90% V0M centrality class

Antitriton spectrum in 50-90% V0M centrality class

Coalescence parameter $B_2$ as a function of $p_{\mathrm{T}}$ in 0-5% V0M centrality class

Coalescence parameter $B_2$ as a function of $p_{\mathrm{T}}$ in 5-10% V0M centrality class

Coalescence parameter $B_2$ as a function of $p_{\mathrm{T}}$ in 10-20% V0M centrality class

Coalescence parameter $B_2$ as a function of $p_{\mathrm{T}}$ in 20-30% V0M centrality class

Coalescence parameter $B_2$ as a function of $p_{\mathrm{T}}$ in 30-40% V0M centrality class

Coalescence parameter $B_2$ as a function of $p_{\mathrm{T}}$ in 40-50% V0M centrality class

Coalescence parameter $B_2$ as a function of $p_{\mathrm{T}}$ in 50-60% V0M centrality class

Coalescence parameter $B_2$ as a function of $p_{\mathrm{T}}$ in 60-70% V0M centrality class

Coalescence parameter $B_2$ as a function of $p_{\mathrm{T}}$ in 70-80% V0M centrality class

Coalescence parameter $B_2$ as a function of $p_{\mathrm{T}}$ in 80-90% V0M centrality class

Coalescence parameter $B_3$ from anti$^3$He as a function of $p_{\mathrm{T}}$ in 0-5% V0M centrality class

Coalescence parameter $B_3$ from anti$^3$He as a function of $p_{\mathrm{T}}$ in 5-10% V0M centrality class

Coalescence parameter $B_3$ from anti$^3$He as a function of $p_{\mathrm{T}}$ in 10-30% V0M centrality class

Coalescence parameter $B_3$ from anti$^3$He as a function of $p_{\mathrm{T}}$ in 30-50% V0M centrality class

Coalescence parameter $B_3$ from anti$^3$He as a function of $p_{\mathrm{T}}$ in 50-90% V0M centrality class

Coalescence parameter $B_3$ from antitriton as a function of $p_{\mathrm{T}}$ in 0-10% V0M centrality class

Coalescence parameter $B_3$ from antitriton as a function of $p_{\mathrm{T}}$ in 10-30% V0M centrality class

Coalescence parameter $B_3$ from antitriton as a function of $p_{\mathrm{T}}$ in 30-50% V0M centrality class

Coalescence parameter $B_3$ from antitriton as a function of $p_{\mathrm{T}}$ in 50-90% V0M centrality class

Deuteron over proton ratio in Pb-Pb collisions as a function of the charged particle multiplicity density at mid-rapidity

$^3$He over proton ratio in Pb-Pb collisions as a function of the charged particle multiplicity density at mid-rapidity

Triton over proton ratio in Pb-Pb collisions as a function of the charged particle multiplicity density at mid-rapidity

Triton over $^3$He ratio in Pb-Pb collisions as a function $p_{\mathrm{T}}$ in 0-10% V0M centrality class

Triton over $^3$He ratio in Pb-Pb collisions as a function $p_{\mathrm{T}}$ in 10-30% V0M centrality class

Triton over $^3$He ratio in Pb-Pb collisions as a function $p_{\mathrm{T}}$ in 30-50% V0M centrality class

Triton over $^3$He ratio in Pb-Pb collisions as a function $p_{\mathrm{T}}$ in 50-90% V0M centrality class

Triton over He3 ratio in Pb-Pb collisions as a function of the charged particle multiplicity density at mid-rapidity

pT-integrated yields of deuteron in Pb-Pb collisions as a function of the charged particle multiplicity density at mid-rapidity

pT-integrated yields of antideuteron in Pb-Pb collisions as a function of the charged particle multiplicity density at mid-rapidity

meanpT of deuteron in Pb-Pb collisions as a function of the charged particle multiplicity density at mid-rapidity

meanpT of antideuteron in Pb-Pb collisions as a function of the charged particle multiplicity density at mid-rapidity

pT-integrated yields of ${}^{3}$He in Pb-Pb collisions as a function of the charged particle multiplicity density at mid-rapidity

pT-integrated yields of anti${}^{3}$He in Pb-Pb collisions as a function of the charged particle multiplicity density at mid-rapidity

meanpTs of ${}^{3}$He in Pb-Pb collisions as a function of the charged particle multiplicity density at mid-rapidity

meanpT of anti${}^{3}$He in Pb-Pb collisions as a function of the charged particle multiplicity density at mid-rapidity

pT-integrated yields of Antitriton in Pb-Pb collisions as a function of the charged particle multiplicity density at mid-rapidity

meanpT of Antitriton in Pb-Pb collisions as a function of the charged particle multiplicity density at mid-rapidity

Two-particle transverse momentum correlation $G_{2}^{\rm CI}$ for 0$-$5% multiplicity class pp collisions at $\sqrt{s}=7\;\text{TeV}$.

Two-particle transverse momentum correlation $G_{2}^{\rm CI}$ for 30$-$40% multiplicity class pp collisions at $\sqrt{s}=7\;\text{TeV}$.

Two-particle transverse momentum correlation $G_{2}^{\rm CI}$ for 70$-$80% multiplicity class pp collisions at $\sqrt{s}=7\;\text{TeV}$.

Two-particle transverse momentum correlation $G_{2}^{\rm CD}$ for 0$-$5% multiplicity class p$-$Pb collisions at $\sqrt{s_{\rm NN}}=5.02\;\text{TeV}$.

Two-particle transverse momentum correlation $G_{2}^{\rm CD}$ for 30$-$40% multiplicity class p$-$Pb collisions at $\sqrt{s_{\rm NN}}=5.02\;\text{TeV}$.

Two-particle transverse momentum correlation $G_{2}^{\rm CD}$ for 70$-$80% multiplicity class p$-$Pb collisions at $\sqrt{s_{\rm NN}}=5.02\;\text{TeV}$.

Two-particle transverse momentum correlation $G_{2}^{\rm CI}$ for 0$-$5% multiplicity class p$-$Pb collisions at $\sqrt{s_{\rm NN}}=5.02\;\text{TeV}$.

Two-particle transverse momentum correlation $G_{2}^{\rm CI}$ for 30$-$40% multiplicity class p$-$Pb collisions at $\sqrt{s_{\rm NN}}=5.02\;\text{TeV}$.

Two-particle transverse momentum correlation $G_{2}^{\rm CI}$ for 70$-$80% multiplicity class p$-$Pb collisions at $\sqrt{s_{\rm NN}}=5.02\;\text{TeV}$.

Near side ($|\Delta\varphi| < \pi/2$) longitudinal projection of the two-particle transverse momentum correlation $G_{2}^{\rm CD}$ for 0$-$5%, 30$-$40%, and 70$-$80% multiplicity classes pp collisions at $\sqrt{s}=7\;\text{TeV}$. Systematic uncertainty on the long-range mean correlator strength $\delta B = 3.7\times 10^{-3}$, $5.8\times 10^{-3}$, and $6.5\times 10^{-3}$, respectively.

Azimuthal projection ($|\Delta\eta|<1.6$) of the two-particle transverse momentum correlation $G_{2}^{\rm CD}$ for 0$-$5%, 30$-$40%, and 70$-$80% multiplicity classes pp collisions at $\sqrt{s}=7\;\text{TeV}$. Systematic uncertainty on the long-range mean correlator strength $\delta B = 2.1\times 10^{-3}$, $4.3\times 10^{-3}$, and $7.7\times 10^{-3}$, respectively.

Near side ($|\Delta\varphi| < \pi/2$) longitudinal projection of the two-particle transverse momentum correlation $G_{2}^{\rm CI}$ for 0$-$5%, 30$-$40%, and 70$-$80% multiplicity classes pp collisions at $\sqrt{s}=7\;\text{TeV}$. Systematic uncertainty on the long-range mean correlator strength $\delta B = 2.8\times 10^{-3}$, $6.6\times 10^{-3}$, and $2.9\times 10^{-2}$, respectively.

Azimuthal projection ($|\Delta\eta|<1.6$) of the two-particle transverse momentum correlation $G_{2}^{\rm CI}$ for 0$-$5%, 30$-$40%, and 70$-$80% multiplicity classes pp collisions at $\sqrt{s}=7\;\text{TeV}$. Systematic uncertainty on the long-range mean correlator strength $\delta B = 1.4\times 10^{-3}$, $7.2\times 10^{-3}$, and $2.6\times 10^{-2}$, respectively.

Near side ($|\Delta\varphi| < \pi/2$) longitudinal projection of the two-particle transverse momentum correlation $G_{2}^{\rm CD}$ for 0$-$5%, 30$-$40%, and 70$-$80% multiplicity classes p$-$Pb collisions at $\sqrt{s_{\rm NN}}=5.02\;\text{TeV}$. Systematic uncertainty on the long-range mean correlator strength $\delta B = 1.5\times 10^{-3}$, $2.7\times 10^{-3}$, and $5.0\times 10^{-3}$, respectively.

Azimuthal projection ($|\Delta\eta|<1.6$) of the two-particle transverse momentum correlation $G_{2}^{\rm CD}$ for 0$-$5%, 30$-$40%, and 70$-$80% multiplicity classes p$-$Pb collisions at $\sqrt{s_{\rm NN}}=5.02\;\text{TeV}$. Systematic uncertainty on the long-range mean correlator strength $\delta B = 7.5\times 10^{-4}$, $1.6\times 10^{-3}$, and $3.6\times 10^{-3}$, respectively.

Near side ($|\Delta\varphi| < \pi/2$) longitudinal projection of the two-particle transverse momentum correlation $G_{2}^{\rm CI}$ for 0$-$5%, 30$-$40%, and 70$-$80% multiplicity classes p$-$Pb collisions at $\sqrt{s_{\rm NN}}=5.02\;\text{TeV}$. Systematic uncertainty on the long-range mean correlator strength $\delta B = 9.3\times 10^{-5}$, $8.1\times 10^{-4}$, and $6.7\times 10^{-3}$, respectively.

Azimuthal projection ($|\Delta\eta|<1.6$) of the two-particle transverse momentum correlation $G_{2}^{\rm CI}$ for 0$-$5%, 30$-$40%, and 70$-$80% multiplicity classes p$-$Pb collisions at $\sqrt{s_{\rm NN}}=5.02\;\text{TeV}$. Systematic uncertainty on the long-range mean correlator strength $\delta B = 4.0\times 10^{-4}$, $1.5\times 10^{-3}$, and $7.5\times 10^{-3}$, respectively.

Evolution with the average charged particle multiplicity of the longitudinal widths of the two-particle transverse momentum differential correlation $G_{2}^{\rm CD}$ in pp and p$-$Pb collisions at $\sqrt{s} = 7\;\text{TeV}$ and $\sqrt{s_{\rm NN}} = 5.02\;\text{TeV}$, respectively. Vertical bars (mostly smaller than the marker size) and filled boxes represent statistical and systematic uncertainties, respectively.

Evolution with the average charged particle multiplicity of the azimuthal widths of the two-particle transverse momentum differential correlation $G_{2}^{\rm CD}$ in pp and p$-$Pb collisions at $\sqrt{s} = 7\;\text{TeV}$ and $\sqrt{s_{\rm NN}} = 5.02\;\text{TeV}$, respectively. Vertical bars (mostly smaller than the marker size) and filled boxes represent statistical and systematic uncertainties, respectively.

Evolution with the average charged particle multiplicity of the longitudinal widths of the two-particle transverse momentum differential correlation $G_{2}^{\rm CI}$ in pp and p$-$Pb collisions at $\sqrt{s} = 7\;\text{TeV}$ and $\sqrt{s_{\rm NN}} = 5.02\;\text{TeV}$, respectively. Vertical bars (mostly smaller than the marker size) and filled boxes represent statistical and systematic uncertainties, respectively.

Evolution with the average charged particle multiplicity of the azimuthal widths of the two-particle transverse momentum differential correlation $G_{2}^{\rm CI}$ in pp and p$-$Pb collisions at $\sqrt{s} = 7\;\text{TeV}$ and $\sqrt{s_{\rm NN}} = 5.02\;\text{TeV}$, respectively. Vertical bars (mostly smaller than the marker size) and filled boxes represent statistical and systematic uncertainties, respectively.

$p_{\rm T}$-differential density of $\Xi^{\pm}$ in jets and the underlying event in pp collisions at $\sqrt{s} = 13$ TeV.

$p_{\rm T}$-differential density of inclusive $\Omega^{\pm}$ in pp collisions at $\sqrt{s} = 13$ TeV.

$p_{\rm T}$-differential density of $\Omega^{\pm}$ in jets and the underlying event in pp collisions at $\sqrt{s} = 13$ TeV.

$p_{\rm T}$-differential $(\Lambda + \overline{\Lambda})/2{\rm K}_{\rm S}^{0}$ ratio of inclusive particles in pp collisions at $\sqrt{s} = 13$ TeV.

$p_{\rm T}$-differential $(\Lambda + \overline{\Lambda})/2{\rm K}_{\rm S}^{0}$ ratio in jets and the underlying event in pp collisions at $\sqrt{s} = 13$ TeV.

$p_{\rm T}$-differential $(\Xi^{-} + \Xi^{+}) / 2{\rm K}_{\rm S}^{0}$ and $(\Xi^{-} + \Xi^{+}) / (\Lambda + \overline{\Lambda})$ ratios of inclusive particles in pp collisions at $\sqrt{s} = 13$ TeV.

$p_{\rm T}$-differential $(\Xi^{-} + \Xi^{+}) / 2{\rm K}_{\rm S}^{0}$ and $(\Xi^{-} + \Xi^{+}) / (\Lambda + \overline{\Lambda})$ ratios in jets and the underlying event in pp collisions at $\sqrt{s} = 13$ TeV.

$p_{\rm T}$-differential $(\Omega^{-} + \Omega^{+}) / 2{\rm K}_{\rm S}^{0}$, $(\Omega^{-} + \Omega^{+}) / (\Lambda + \overline{\Lambda})$ and $(\Omega^{-} + \Omega^{+}) / (\Xi^{-} + \Xi^{+})$ ratios of inclusive particles in pp collisions at $\sqrt{s} = 13$ TeV.

$p_{\rm T}$-differential $(\Omega^{-} + \Omega^{+}) / 2{\rm K}_{\rm S}^{0}$, $(\Omega^{-} + \Omega^{+}) / (\Lambda + \overline{\Lambda})$ and $(\Omega^{-} + \Omega^{+}) / (\Xi^{-} + \Xi^{+})$ ratios in jets and the underlying event in pp collisions at $\sqrt{s} = 13$ TeV.

$p_{\rm T}$-differential density of inclusive ${\rm K}_{\rm S}^{0}$ and $\Lambda$ ($\overline{\Lambda}$) in p-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV.

$p_{\rm T}$-differential densities of ${\rm K}_{\rm S}^{0}$ and $\Lambda$ ($\overline{\Lambda}$) in jets and the underlying event in p-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV.

$p_{\rm T}$-differential density of inclusive $\Xi^{\pm}$ in p-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV.

$p_{\rm T}$-differential density of $\Xi^{\pm}$ in jets and the underlying event in p-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV.

$p_{\rm T}$-differential density of inclusive $\Omega^{\pm}$ in p-Pb collisions at $\sqrt{s} = 5.02$ TeV.

$p_{\rm T}$-differential density of $\Omega^{\pm}$ in jets and the underlying event in p-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV.

$p_{\rm T}$-differential $(\Lambda + \overline{\Lambda})/2{\rm K}_{\rm S}^{0}$ ratio in jets for various event activity classes in p-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV.

$p_{\rm T}$-differential $(\Xi^{-} + \Xi^{+}) / 2{\rm K}_{\rm S}^{0}$ and $(\Xi^{-} + \Xi^{+}) / (\Lambda + \overline{\Lambda})$ ratios in jets for various event activity classes in p-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV.

$p_{\rm T}$-differential $(\Omega^{-} + \Omega^{+}) / 2{\rm K}_{\rm S}^{0}$, $(\Omega^{-} + \Omega^{+}) / (\Lambda + \overline{\Lambda})$ and $(\Omega^{-} + \Omega^{+}) / (\Xi^{-} + \Xi^{+})$ ratios in jets in MB p-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV.

$p_{\rm T}$-differential density of inclusive ${\rm K}_{\rm S}^{0}$ and $\Lambda$ ($\overline{\Lambda}$) for $0$-$10\%$ event activity class in p-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV.

$p_{\rm T}$-differential densities of ${\rm K}_{\rm S}^{0}$ and $\Lambda$ ($\overline{\Lambda}$) in jets and the underlying event for $0$-$10\%$ event activity class in p-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV.

$p_{\rm T}$-differential density of inclusive $\Xi^{\pm}$ for $0$-$10\%$ event activity class in p-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV.

$p_{\rm T}$-differential density of $\Xi^{\pm}$ in jets and the underlying event for $0$-$10\%$ event activity class in p-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV.

$p_{\rm T}$-differential density of inclusive ${\rm K}_{\rm S}^{0}$ and $\Lambda$ ($\overline{\Lambda}$) for $10$-$40\%$ event activity class in p-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV.

$p_{\rm T}$-differential densities of ${\rm K}_{\rm S}^{0}$ and $\Lambda$ ($\overline{\Lambda}$) in jets and the underlying event for $10$-$40\%$ event activity class in p-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV.

$p_{\rm T}$-differential density of inclusive $\Xi^{\pm}$ for $10$-$40\%$ event activity class in p-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV.

$p_{\rm T}$-differential density of $\Xi^{\pm}$ in jets and the underlying event for $10$-$40\%$ event activity class in p-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV.

$p_{\rm T}$-differential density of inclusive ${\rm K}_{\rm S}^{0}$ and $\Lambda$ ($\overline{\Lambda}$) for $40$-$100\%$ event activity class in p-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV.

$p_{\rm T}$-differential densities of ${\rm K}_{\rm S}^{0}$ and $\Lambda$ ($\overline{\Lambda}$) in jets and the underlying event for $40$-$100\%$ event activity class in p-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV.

$p_{\rm T}$-differential density of inclusive $\Xi^{\pm}$ for $40$-$100\%$ event activity class in p-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV.

$p_{\rm T}$-differential density of $\Xi^{\pm}$ in jets and the underlying event for $40$-$100\%$ event activity class in p-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV.

$p_{\rm T}$-differential $(\Lambda + \overline{\Lambda})/2{\rm K}_{\rm S}^{0}$ ratio of inclusive particles for various event activity classes in p-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV.

$p_{\rm T}$-differential $(\Lambda + \overline{\Lambda})/2{\rm K}_{\rm S}^{0}$ ratio in the underlying event for various event activity classes in p-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV.

$p_{\rm T}$-differential $(\Lambda + \overline{\Lambda})/2{\rm K}_{\rm S}^{0}$ ratio in jets for various event activity classes in p-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV.

$p_{\rm T}$-differential $(\Xi^{-} + \Xi^{+}) / 2{\rm K}_{\rm S}^{0}$ ratio of inclusive particles for various event activity classes in p-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV.

$p_{\rm T}$-differential $(\Xi^{-} + \Xi^{+}) / 2{\rm K}_{\rm S}^{0}$ ratio in the underlying event for $0$-$10\%$ event activity class in p-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV.

$p_{\rm T}$-differential $(\Xi^{-} + \Xi^{+}) / 2{\rm K}_{\rm S}^{0}$ ratio in the underlying event for $10$-$40\%$ and $40$-$100\%$ event activity classes in p-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV.

$p_{\rm T}$-differential $(\Xi^{-} + \Xi^{+}) / 2{\rm K}_{\rm S}^{0}$ ratio in jets for various event activity classes in p-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV.

$p_{\rm T}$-differential $(\Xi^{-} + \Xi^{+}) / (\Lambda + \overline{\Lambda})$ ratio of inclusive particles for various event activity classes in p-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV.

$p_{\rm T}$-differential $(\Xi^{-} + \Xi^{+}) / (\Lambda + \overline{\Lambda})$ ratio in the underlying event for $0$-$10\%$ event activity class in p-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV.

$p_{\rm T}$-differential $(\Xi^{-} + \Xi^{+}) / (\Lambda + \overline{\Lambda})$ ratio in the underlying event for $10$-$40\%$ and $40$-$100\%$ event activity classes in p-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV.

$p_{\rm T}$-differential $(\Xi^{-} + \Xi^{+}) / (\Lambda + \overline{\Lambda})$ ratio in jets for various event activity classes in p-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=2$) for jets of $R=0.2$, in the interval $20<p_{\rm T}^{\rm ch \ jet}<40 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=3$) for jets of $R=0.2$, in the interval $20<p_{\rm T}^{\rm ch \ jet}<40 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.2,\beta=1$) for jets of $R=0.2$, in the interval $20<p_{\rm T}^{\rm ch \ jet}<40 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.3,\beta=1$) for jets of $R=0.2$, in the interval $20<p_{\rm T}^{\rm ch \ jet}<40 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.3,\beta=1$) for jets of $R=0.2$, in the interval $20<p_{\rm T}^{\rm ch \ jet}<40 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.2,\beta=1$) for jets of $R=0.2$, in the interval $20<p_{\rm T}^{\rm ch \ jet}<40 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=0$) for jets of $R=0.2$, in the interval $20<p_{\rm T}^{\rm ch \ jet}<40 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=1$) for jets of $R=0.2$, in the interval $20<p_{\rm T}^{\rm ch \ jet}<40 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=2$) for jets of $R=0.2$, in the interval $20<p_{\rm T}^{\rm ch \ jet}<40 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=3$) for jets of $R=0.2$, in the interval $20<p_{\rm T}^{\rm ch \ jet}<40 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$Standard for jets of $R=0.2$, in the interval $40<p_{\rm T}^{\rm ch \ jet}<60 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=0$) for jets of $R=0.2$, in the interval $40<p_{\rm T}^{\rm ch \ jet}<60 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=1$) for jets of $R=0.2$, in the interval $40<p_{\rm T}^{\rm ch \ jet}<60 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=2$) for jets of $R=0.2$, in the interval $40<p_{\rm T}^{\rm ch \ jet}<60 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=3$) for jets of $R=0.2$, in the interval $40<p_{\rm T}^{\rm ch \ jet}<60 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.2,\beta=1$) for jets of $R=0.2$, in the interval $40<p_{\rm T}^{\rm ch \ jet}<60 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.3,\beta=1$) for jets of $R=0.2$, in the interval $40<p_{\rm T}^{\rm ch \ jet}<60 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.3,\beta=1$) for jets of $R=0.2$, in the interval $40<p_{\rm T}^{\rm ch \ jet}<60 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.2,\beta=1$) for jets of $R=0.2$, in the interval $40<p_{\rm T}^{\rm ch \ jet}<60 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=0$) for jets of $R=0.2$, in the interval $40<p_{\rm T}^{\rm ch \ jet}<60 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=1$) for jets of $R=0.2$, in the interval $40<p_{\rm T}^{\rm ch \ jet}<60 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=2$) for jets of $R=0.2$, in the interval $40<p_{\rm T}^{\rm ch \ jet}<60 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=3$) for jets of $R=0.2$, in the interval $40<p_{\rm T}^{\rm ch \ jet}<60 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$Standard for jets of $R=0.2$, in the interval $60<p_{\rm T}^{\rm ch \ jet}<80 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=0$) for jets of $R=0.2$, in the interval $60<p_{\rm T}^{\rm ch \ jet}<80 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=1$) for jets of $R=0.2$, in the interval $60<p_{\rm T}^{\rm ch \ jet}<80 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=2$) for jets of $R=0.2$, in the interval $60<p_{\rm T}^{\rm ch \ jet}<80 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=3$) for jets of $R=0.2$, in the interval $60<p_{\rm T}^{\rm ch \ jet}<80 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.2,\beta=1$) for jets of $R=0.2$, in the interval $60<p_{\rm T}^{\rm ch \ jet}<80 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.3,\beta=1$) for jets of $R=0.2$, in the interval $60<p_{\rm T}^{\rm ch \ jet}<80 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.3,\beta=1$) for jets of $R=0.2$, in the interval $60<p_{\rm T}^{\rm ch \ jet}<80 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.2,\beta=1$) for jets of $R=0.2$, in the interval $60<p_{\rm T}^{\rm ch \ jet}<80 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=0$) for jets of $R=0.2$, in the interval $60<p_{\rm T}^{\rm ch \ jet}<80 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=1$) for jets of $R=0.2$, in the interval $60<p_{\rm T}^{\rm ch \ jet}<80 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=2$) for jets of $R=0.2$, in the interval $60<p_{\rm T}^{\rm ch \ jet}<80 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=3$) for jets of $R=0.2$, in the interval $60<p_{\rm T}^{\rm ch \ jet}<80 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$Standard for jets of $R=0.2$, in the interval $80<p_{\rm T}^{\rm ch \ jet}<100 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=0$) for jets of $R=0.2$, in the interval $80<p_{\rm T}^{\rm ch \ jet}<100 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=1$) for jets of $R=0.2$, in the interval $80<p_{\rm T}^{\rm ch \ jet}<100 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=2$) for jets of $R=0.2$, in the interval $80<p_{\rm T}^{\rm ch \ jet}<100 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=3$) for jets of $R=0.2$, in the interval $80<p_{\rm T}^{\rm ch \ jet}<100 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.2,\beta=1$) for jets of $R=0.2$, in the interval $80<p_{\rm T}^{\rm ch \ jet}<100 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.3,\beta=1$) for jets of $R=0.2$, in the interval $80<p_{\rm T}^{\rm ch \ jet}<100 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.3,\beta=1$) for jets of $R=0.2$, in the interval $80<p_{\rm T}^{\rm ch \ jet}<100 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.2,\beta=1$) for jets of $R=0.2$, in the interval $80<p_{\rm T}^{\rm ch \ jet}<100 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=0$) for jets of $R=0.2$, in the interval $80<p_{\rm T}^{\rm ch \ jet}<100 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=1$) for jets of $R=0.2$, in the interval $80<p_{\rm T}^{\rm ch \ jet}<100 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=2$) for jets of $R=0.2$, in the interval $80<p_{\rm T}^{\rm ch \ jet}<100 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=3$) for jets of $R=0.2$, in the interval $80<p_{\rm T}^{\rm ch \ jet}<100 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$Standard for jets of $R=0.4$, in the interval $20<p_{\rm T}^{\rm ch \ jet}<40 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=0$) for jets of $R=0.4$, in the interval $20<p_{\rm T}^{\rm ch \ jet}<40 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=1$) for jets of $R=0.4$, in the interval $20<p_{\rm T}^{\rm ch \ jet}<40 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=2$) for jets of $R=0.4$, in the interval $20<p_{\rm T}^{\rm ch \ jet}<40 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=3$) for jets of $R=0.4$, in the interval $20<p_{\rm T}^{\rm ch \ jet}<40 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.2,\beta=1$) for jets of $R=0.4$, in the interval $20<p_{\rm T}^{\rm ch \ jet}<40 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.3,\beta=1$) for jets of $R=0.4$, in the interval $20<p_{\rm T}^{\rm ch \ jet}<40 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.3,\beta=1$) for jets of $R=0.4$, in the interval $20<p_{\rm T}^{\rm ch \ jet}<40 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.2,\beta=1$) for jets of $R=0.4$, in the interval $20<p_{\rm T}^{\rm ch \ jet}<40 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=0$) for jets of $R=0.4$, in the interval $20<p_{\rm T}^{\rm ch \ jet}<40 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=1$) for jets of $R=0.4$, in the interval $20<p_{\rm T}^{\rm ch \ jet}<40 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=2$) for jets of $R=0.4$, in the interval $20<p_{\rm T}^{\rm ch \ jet}<40 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=3$) for jets of $R=0.4$, in the interval $20<p_{\rm T}^{\rm ch \ jet}<40 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$Standard for jets of $R=0.4$, in the interval $40<p_{\rm T}^{\rm ch \ jet}<60 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=0$) for jets of $R=0.4$, in the interval $40<p_{\rm T}^{\rm ch \ jet}<60 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=1$) for jets of $R=0.4$, in the interval $40<p_{\rm T}^{\rm ch \ jet}<60 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=2$) for jets of $R=0.4$, in the interval $40<p_{\rm T}^{\rm ch \ jet}<60 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=3$) for jets of $R=0.4$, in the interval $40<p_{\rm T}^{\rm ch \ jet}<60 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.2,\beta=1$) for jets of $R=0.4$, in the interval $40<p_{\rm T}^{\rm ch \ jet}<60 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.3,\beta=1$) for jets of $R=0.4$, in the interval $40<p_{\rm T}^{\rm ch \ jet}<60 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.3,\beta=1$) for jets of $R=0.4$, in the interval $40<p_{\rm T}^{\rm ch \ jet}<60 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.2,\beta=1$) for jets of $R=0.4$, in the interval $40<p_{\rm T}^{\rm ch \ jet}<60 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=0$) for jets of $R=0.4$, in the interval $40<p_{\rm T}^{\rm ch \ jet}<60 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=1$) for jets of $R=0.4$, in the interval $40<p_{\rm T}^{\rm ch \ jet}<60 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=2$) for jets of $R=0.4$, in the interval $40<p_{\rm T}^{\rm ch \ jet}<60 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=3$) for jets of $R=0.4$, in the interval $40<p_{\rm T}^{\rm ch \ jet}<60 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$Standard for jets of $R=0.4$, in the interval $60<p_{\rm T}^{\rm ch \ jet}<80 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=0$) for jets of $R=0.4$, in the interval $60<p_{\rm T}^{\rm ch \ jet}<80 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=1$) for jets of $R=0.4$, in the interval $60<p_{\rm T}^{\rm ch \ jet}<80 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=2$) for jets of $R=0.4$, in the interval $60<p_{\rm T}^{\rm ch \ jet}<80 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=3$) for jets of $R=0.4$, in the interval $60<p_{\rm T}^{\rm ch \ jet}<80 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.2,\beta=1$) for jets of $R=0.4$, in the interval $60<p_{\rm T}^{\rm ch \ jet}<80 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.3,\beta=1$) for jets of $R=0.4$, in the interval $60<p_{\rm T}^{\rm ch \ jet}<80 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.3,\beta=1$) for jets of $R=0.4$, in the interval $60<p_{\rm T}^{\rm ch \ jet}<80 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.2,\beta=1$) for jets of $R=0.4$, in the interval $60<p_{\rm T}^{\rm ch \ jet}<80 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=0$) for jets of $R=0.4$, in the interval $60<p_{\rm T}^{\rm ch \ jet}<80 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=1$) for jets of $R=0.4$, in the interval $60<p_{\rm T}^{\rm ch \ jet}<80 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=2$) for jets of $R=0.4$, in the interval $60<p_{\rm T}^{\rm ch \ jet}<80 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=3$) for jets of $R=0.4$, in the interval $60<p_{\rm T}^{\rm ch \ jet}<80 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$Standard for jets of $R=0.4$, in the interval $80<p_{\rm T}^{\rm ch \ jet}<100 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=0$) for jets of $R=0.4$, in the interval $80<p_{\rm T}^{\rm ch \ jet}<100 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=1$) for jets of $R=0.4$, in the interval $80<p_{\rm T}^{\rm ch \ jet}<100 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=2$) for jets of $R=0.4$, in the interval $80<p_{\rm T}^{\rm ch \ jet}<100 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=3$) for jets of $R=0.4$, in the interval $80<p_{\rm T}^{\rm ch \ jet}<100 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.2,\beta=1$) for jets of $R=0.4$, in the interval $80<p_{\rm T}^{\rm ch \ jet}<100 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.3,\beta=1$) for jets of $R=0.4$, in the interval $80<p_{\rm T}^{\rm ch \ jet}<100 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.3,\beta=1$) for jets of $R=0.4$, in the interval $80<p_{\rm T}^{\rm ch \ jet}<100 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.2,\beta=1$) for jets of $R=0.4$, in the interval $80<p_{\rm T}^{\rm ch \ jet}<100 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=0$) for jets of $R=0.4$, in the interval $80<p_{\rm T}^{\rm ch \ jet}<100 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=1$) for jets of $R=0.4$, in the interval $80<p_{\rm T}^{\rm ch \ jet}<100 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=2$) for jets of $R=0.4$, in the interval $80<p_{\rm T}^{\rm ch \ jet}<100 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=3$) for jets of $R=0.4$, in the interval $80<p_{\rm T}^{\rm ch \ jet}<100 \ {\rm GeV}/c$.

Distribution of the most-probable value of the WTA$\textendash$Standard spectra as a function of $p_{\rm T}^{\rm ch \ jet}$ for $R=0.2$.

Distribution of the most-probable value of the WTA$\textendash$Standard spectra as a function of $p_{\rm T}^{\rm ch \ jet}$ for $R=0.4$.

Probability of finding at least one TAR jet, where the p_T-leading TAR jet passes the m_Wcand and D₂^&beta;=1 requirements, as a function of m_s. The probability is determined in a sample of signal events with m_Z'=2100 GeV, with the preselections applied.

Probability of finding a W_had candidate reconstructed as a pair of R=0.4 PFlow jets, as a function of m_s. The probability is determined in a sample of signal events with m_Z'=500 GeV, with the preselections applied that do not pass the requirements of the merged category.

Probability of finding a W_had candidate reconstructed as a pair of R=0.4 PFlow jets, as a function of m_s. The probability is determined in a sample of signal events with m_Z'=1000 GeV, with the preselections applied that do not pass the requirements of the merged category.

Probability of finding a W_had candidate reconstructed as a pair of R=0.4 PFlow jets, as a function of m_s. The probability is determined in a sample of signal events with m_Z'=1700 GeV, with the preselections applied that do not pass the requirements of the merged category.

Probability of finding a W_had candidate reconstructed as a pair of R=0.4 PFlow jets, as a function of m_s. The probability is determined in a sample of signal events with m_Z'=2100 GeV, with the preselections applied that do not pass the requirements of the merged category.

Observed exclusion contour at 95&#37; C.L. for the dark Higgs model in the (m_Z', m_s) plane for g_q=0.25, g_&chi;=1, m_&chi;=200 GeV, and sin&theta;=0.01.

Expected exclusion contour at 95&#37; C.L. for the dark Higgs model in the (m_Z', m_s) plane for g_q=0.25, g_&chi;=1, m_&chi;=200 GeV, and sin&theta;=0.01.

Expected+1&sigma; exclusion contour at 95&#37; C.L. for the dark Higgs model in the (m_Z', m_s) plane for g_q=0.25, g_&chi;=1, m_&chi;=200 GeV, and sin&theta;=0.01.

Expected-1&sigma; exclusion contour at 95&#37; C.L. for the dark Higgs model in the (m_Z', m_s) plane for g_q=0.25, g_&chi;=1, m_&chi;=200 GeV, and sin&theta;=0.01.

Expected+2&sigma; exclusion contour at 95&#37; C.L. for the dark Higgs model in the (m_Z', m_s) plane for g_q=0.25, g_&chi;=1, m_&chi;=200 GeV, and sin&theta;=0.01.

Expected-2&sigma; exclusion contour at 95&#37; C.L. for the dark Higgs model in the (m_Z', m_s) plane for g_q=0.25, g_&chi;=1, m_&chi;=200 GeV, and sin&theta;=0.01.

Observed upper limits at 95&#37; C.L. on &sigma;(pp &rarr; s &chi;&chi;) &times; B(s &rarr; W^&pm; W^&mp;) for m_Z'=0.5 TeV as a function of m_s. The expected limits, varied up and down by one and two standard deviations, are shown as green and yellow bands, respectively. The observed and expected limits are compared to the theoretical LO cross section for the &sigma;(pp &rarr; s &chi;&chi;) &times; B(s &rarr; W^&pm; W^&mp;) process for m_Z'=0.5 TeV, shown in dashed blue.

Observed upper limits at 95&#37; C.L. on &sigma;(pp &rarr; s &chi;&chi;) &times; B(s &rarr; W^&pm; W^&mp;) for m_Z'=1 TeV as a function of m_s. The expected limits, varied up and down by one and two standard deviations, are shown as green and yellow bands, respectively. The observed and expected limits are compared to the theoretical LO cross section for the &sigma;(pp &rarr; s &chi;&chi;) &times; B(s &rarr; W^&pm; W^&mp;) process for m_Z'=1 TeV, shown in dashed blue.

Observed upper limits at 95&#37; C.L. on &sigma;(pp &rarr; s &chi;&chi;) &times; B(s &rarr; W^&pm; W^&mp;) for m_Z'=1.7 TeV as a function of m_s. The expected limits, varied up and down by one and two standard deviations, are shown as green and yellow bands, respectively. The observed and expected limits are compared to the theoretical LO cross section for the &sigma;(pp &rarr; s &chi;&chi;) &times; B(s &rarr; W^&pm; W^&mp;) process for m_Z'=1.7 TeV, shown in dashed blue.

Observed upper limits at 95&#37; C.L. on &sigma;(pp &rarr; s &chi;&chi;) &times; B(s &rarr; W^&pm; W^&mp;) for m_Z'=2.1 TeV as a function of m_s. The expected limits, varied up and down by one and two standard deviations, are shown as green and yellow bands, respectively. The observed and expected limits are compared to the theoretical LO cross section for the &sigma;(pp &rarr; s &chi;&chi;) &times; B(s &rarr; W^&pm; W^&mp;) process for m_Z'=2.1 TeV, shown in dashed blue.

Data overlaid on SM background yields stacked in each SR and CR category after the fit to data ('Post-fit'). The yields in the SR are broken down into their contributions to the individual bins. The maximum-likelihood estimators are set to the conditional values of the CR-only fit, and propagated to SR and CRs.

Dominant sources of uncertainty for three dark Higgs scenarios after the fit to data. The uncertainties are quantified in terms of their contribution to the fitted signal uncertainty that is expressed relative to the theory prediction. Three representative dark Higgs signal scenarios with g_q=0.25, g_&chi;=1.0, sin&theta;=0.01 and m_&chi;=200 GeV are considered, which are indicated using the (m_Z', m_s) format in units of GeV in the table columns.

Cumulative efficiencies in the merged category for three representative dark Higgs signal scenarios with g_q=0.25, g_&chi;=1.0, sin&theta;=0.01, m_Z' = 1 TeV, and m_&chi;=200 GeV considering s&rarr;W(&ell;&nu;)W(qq) decays only.

Cumulative efficiencies in the resolved category for three representative dark Higgs signal scenarios with g_q=0.25, g_&chi;=1.0, sin&theta;=0.01, m_Z' = 1 TeV, and m_&chi;=200 GeV considering s&rarr;W(&ell;&nu;)W(qq) decays only.

Theoretical cross section for &sigma;(pp &rarr; s&chi;&chi;) &times; B(s &rarr; W^&plusmn;W^&#8723;) for each of the dark Higgs signal points at m_Z′ ={300, 350, 400, 500, 750} GeV, with g_q = 0.25, g<sub>&chi; = 1.0, sin&theta; = 0.01, m_Z′ = 1 TeV , and m_&chi; = 200 GeV. Also shown are experimentally excluded cross sections of &sigma;(pp &rarr; s&chi;&chi;) &times; B(s &rarr; W^&plusmn;W^&#8723;) (Obs.) together with the expectations (Exp.) varied up and down by one standard deviation (&plusmn;1&sigma;).

Theoretical cross section for &sigma;(pp &rarr; s&chi;&chi;) &times; B(s &rarr; W^&plusmn;W^&#8723;) for each of the dark Higgs signal points at m_Z′ ={1000, 1700} GeV, with g_q = 0.25, g<sub>&chi; = 1.0, sin&theta; = 0.01, m_Z′ = 1 TeV , and m_&chi; = 200 GeV. Also shown are experimentally excluded cross sections of &sigma;(pp &rarr; s&chi;&chi;) &times; B(s &rarr; W^&plusmn;W^&#8723;) (Obs.) together with the expectations (Exp.) varied up and down by one standard deviation (&plusmn;1&sigma;).

Theoretical cross section for &sigma;(pp &rarr; s&chi;&chi;) &times; B(s &rarr; W^&plusmn;W^&#8723;) for each of the dark Higgs signal points at m_Z′ ={2100, 2500, 2900, 3300} GeV, with g_q = 0.25, g<sub>&chi; = 1.0, sin&theta; = 0.01, m_Z′ = 1 TeV , and m_&chi; = 200 GeV. Also shown are experimentally excluded cross sections of &sigma;(pp &rarr; s&chi;&chi;) &times; B(s &rarr; W^&plusmn;W^&#8723;) (Obs.) together with the expectations (Exp.) varied up and down by one standard deviation (&plusmn;1&sigma;).

Parametrization of the $A_{X}$ factor, defined as the fraction of diphoton resonances satisfying the fiducial acceptance at the particle level, as function of $m_{X}$ obtained from the narrow width simulated signal samples produced in gluon fusion.

The correction factor, $C_{X}$, defined as the ratio between the number of reconstructed signal events passing the analysis cuts and the number of signal events at the particle level generated within the fiducial volume, and acceptance correction factor, $A_{X}$, defined as the fraction of diphoton resonances satisfying the fiducial acceptance at the particle level. Both are computed for NWA spin-0 models as a function of $m_{X}$.

Effect of event selections on a scalar MC signal sample generated for $m_{X}$ = 15 GeV and on the data. For the MC sample, the efficiencies are shown after applying event weights and a truth level filter that requires two photons with $p^{\gamma\gamma}_{T}>40$ GeV; for the data, the absolute yields are shown. The initial yields for data include a trigger preselection that is the OR of a list of single photon and diphoton triggers. The "2 $loose$ photons" step includes the kinematic acceptance cuts.

Parameterization of the Double Sided Crystal Ball function parameters describing the scalar mass resolution model as a function of $m_{X}$ [GeV].

Expected 95% CL upper limits with 1-sigma uncertainty on the production of a heavy Higgs boson as functions of fw and fww with mass equal to 300 GeV.

Expected 95% CL upper limits with 2-sigma uncertainty on the production of a heavy Higgs boson as functions of fw and fww with mass equal to 300 GeV.

Observed 95% CL upper limits on the production of a heavy Higgs boson as functions of fw and fww with mass equal to 300 GeV.

Expected 95% CL upper limits on the production of a heavy Higgs boson as functions of fw and fww with mass equal to 600 GeV.

Expected 95% CL upper limits with 1-sigma uncertainty on the production of a heavy Higgs boson as functions of fw and fww with mass equal to 600 GeV.

Expected 95% CL upper limits with 2-sigma uncertainty on the production of a heavy Higgs boson as functions of fw and fww with mass equal to 600 GeV.

Observed 95% CL upper limits on the production of a heavy Higgs boson as functions of fw and fww with mass equal to 600 GeV.

Expected 95% CL upper limits on the production of a heavy Higgs boson as functions of fw and fww with mass equal to 900 GeV.

Expected 95% CL upper limits with 1-sigma uncertainty on the production of a heavy Higgs boson as functions of fw and fww with mass equal to 900 GeV.

Expected 95% CL upper limits with 2-sigma uncertainty on the production of a heavy Higgs boson as functions of fw and fww with mass equal to 900 GeV.

Observed 95% CL upper limits on the production of a heavy Higgs boson as functions of fw and fww with mass equal to 900 GeV.

Observed (black solid curve) and expected (black dashed curve) 95% CL upper limits on the production of a heavy Higgs boson as functions of its mass with ( fW, fWW) fixed at (0, 6200). The green (inner) and yellow (outer) bands represent 1 and 2 sigma uncertainty in the expected limits. Theoretical predictions (red solid curve) as functions of the heavy Higgs boson mass are overlaid.

Observed (black solid curve) and expected (black dashed curve) 95% CL upper limits on the production of a heavy Higgs boson as functions of its mass with ( fW, fWW) fixed at (1350, 0). The green (inner) and yellow (outer) bands represent 1 and 2 sigma uncertainty in the expected limits. Theoretical predictions (red solid curve) as functions of the heavy Higgs boson mass are overlaid.

Pre-fit comparison between data and background in the baseline SR for two of the variables used as input for the BSM pBDT: HT.

Data and post-fit background comparison for the distributions of the discriminant variables fitted in the control regions obtained with the background-only fit: CR HF e.

Data and post-fit background comparison for the distributions of the discriminant variables fitted in the control regions obtained with the background-only fit: CR HF mu.

Data and post-fit background comparison for the distributions of the discriminant variables fitted in the control regions obtained with the background-only fit: CR Conv.

Data and post-fit background comparison for the distributions of the discriminant variables fitted in the control regions obtained with the background-only fit: CR ttW.

Data and post-fit background comparison for the distributions of the discriminant variables fitted in the control regions obtained with the background-only fit: CR lowBDT.

Data and post-fit background comparison obtained with the background-only fit in the validation region defined for ttW+jets events: number of jets.

Data and post-fit background comparison obtained with the background-only fit in the validation region defined for ttW+jets events: SM BDT.

Data and post-fit background comparison obtained with the background-only fit to the BSM SR for the BSM pBDT distribution used for mH = 400 GeV.

Data and post-fit background comparison obtained with the background-only fit to the BSM SR for the BSM pBDT distribution used for mH = 1000 GeV.

Observed (black solid line) and expected (black dashed line) 95% CL upper limits on the ttH/A cross-section times branching fraction of H/A->tt as a function of mH/A.

Observed (red line) and expected (black dashed line) exclusion regions at 95% CL in the tan(beta) versus mass plane assuming that both, a heavy scalar H and pseudo-scalar A, contribute to the tttt final state and have the same mass mH=mA.

Observed (red line) and expected (black dashed line) exclusion regions at 95% CL in the tan(beta) versus mass plane assuming that only the scalar H contributes to the tttt final state.

Data and post-fit background comparison obtained with the background-only fit to the BSM SR for the BSM pBDT distribution used for mH = 500 GeV.

Data and post-fit background comparison obtained with the background-only fit to the BSM SR for the BSM pBDT distribution used for mH = 600 GeV.

Data and post-fit background comparison obtained with the background-only fit to the BSM SR for the BSM pBDT distribution used for mH = 700 GeV.

Data and post-fit background comparison obtained with the background-only fit to the BSM SR for the BSM pBDT distribution used for mH = 800 GeV.

Data and post-fit background comparison obtained with the background-only fit to the BSM SR for the BSM pBDT distribution used for mH = 900 GeV.

Observed (red line) and expected (black dashed line) exclusion regions at 95% CL in the tan(beta) versus mass plane assuming that only the pseudo-scalar A contributes to the tttt final state.

The product of acceptance and efficiency (A×ε), defined as the number of signal events satisfying the full set of selection criteria of the BSM SR, divided by the total number of generated signal events, for the tt̄H(→ tt̄ ) process in a type-II 2HDM for tanβ = 1 for the different heavy Higgs mass hypotheses.

Near-side ratios of V^{0}-triggered yields to charged-hadron triggered (h$-$h) ones, ${{Y}^{K^{0}_{S}-\mathrm{h}}_{\Delta\varphi}}/{{Y}^{\mathrm{h-h}}_{\Delta\varphi}}$ and ${{Y}^{(\Lambda+\overline{\Lambda})-\mathrm{h}}_{\Delta\varphi}}/{{Y}^{\mathrm{h-h}}_{\Delta\varphi}}$ in Pb-Pb collisions.

Away-side ratios of V^{0}-triggered yields to charged-hadron triggered (h$-$h) ones, ${{Y}^{K^{0}_{S}-\mathrm{h}}_{\Delta\varphi}}/{{Y}^{\mathrm{h-h}}_{\Delta\varphi}}$ and ${{Y}^{(\Lambda+\overline{\Lambda})-\mathrm{h}}_{\Delta\varphi}}/{{Y}^{\mathrm{h-h}}_{\Delta\varphi}}$ in Pb-Pb collisions.

Near-side ratios of V^{0}-triggered yields to charged-hadron triggered (h--h) ones, ${{Y}^{K^{0}_{S}-\mathrm{h}}_{\Delta\varphi}}/{{Y}^{\mathrm{h-h}}_{\Delta\varphi}}$ and ${{Y}^{(\Lambda+\overline{\Lambda})-\mathrm{h}}_{\Delta\varphi}}/{{Y}^{\mathrm{h-h}}_{\Delta\varphi}}$ in pp collisions.

Away-side ratios of V^{0}-triggered yields to charged-hadron triggered (h--h) ones, ${{Y}^{K^{0}_{S}-\mathrm{h}}_{\Delta\varphi}}/{{Y}^{\mathrm{h-h}}_{\Delta\varphi}}$ and ${{Y}^{(\Lambda+\overline{\Lambda})-\mathrm{h}}_{\Delta\varphi}}/{{Y}^{\mathrm{h-h}}_{\Delta\varphi}}$ in Pb-Pb collisions.

Jet multiplicity measured for a leading-pT jet ($p_{T1}$) with 400 < $p_{T1}$ < 800 GeV and for an azimuthal separation between the two leading jets of $0 < \Delta\Phi_{1,2} < 150^{\circ}$. The full breakdown of the uncertainties is displayed, with PU corresponding to Pileup, PREF to Trigger Prefering, PTHAT to the hard-scale (renormalization and factorization scales), MISS and FAKE to the inefficienties and background, LUMI to integrated luminosity. With JES, JER and stat. unc. following the notation in the paper.

Jet multiplicity measured for a leading-pT jet ($p_{T1}$) with 400 < $p_{T1}$ < 800 GeV and for an azimuthal separation between the two leading jets of $150 < \Delta\Phi_{1,2} < 170^{\circ}$. The full breakdown of the uncertainties is displayed, with PU corresponding to Pileup, PREF to Trigger Prefering, PTHAT to the hard-scale (renormalization and factorization scales), MISS and FAKE to the inefficienties and background, LUMI to integrated luminosity. With JES, JER and stat. unc. following the notation in the paper.

Jet multiplicity measured for a leading-pT jet ($p_{T1}$) with 400 < $p_{T1}$ < 800 GeV and for an azimuthal separation between the two leading jets of $170 < \Delta\Phi_{1,2} < 180^{\circ}$. The full breakdown of the uncertainties is displayed, with PU corresponding to Pileup, PREF to Trigger Prefering, PTHAT to the hard-scale (renormalization and factorization scales), MISS and FAKE to the inefficienties and background, LUMI to integrated luminosity. With JES, JER and stat. unc. following the notation in the paper.

Jet multiplicity measured for a leading-pT jet ($p_{T1}$) with $p_{T1}$ > 800 and for an azimuthal separation between the two leading jets of $0 < \Delta\Phi_{1,2} < 150^{\circ}$. The full breakdown of the uncertainties is displayed, with PU corresponding to Pileup, PREF to Trigger Prefering, PTHAT to the hard-scale (renormalization and factorization scales), MISS and FAKE to the inefficienties and background, LUMI to integrated luminosity. With JES, JER and stat. unc. following the notation in the paper.

Jet multiplicity measured for a leading-pT jet ($p_{T1}$) with $p_{T1}$ > 800 and for an azimuthal separation between the two leading jets of $150 < \Delta\Phi_{1,2} < 170^{\circ}$. The full breakdown of the uncertainties is displayed, with PU corresponding to Pileup, PREF to Trigger Prefering, PTHAT to the hard-scale (renormalization and factorization scales), MISS and FAKE to the inefficienties and background, LUMI to integrated luminosity. With JES, JER and stat. unc. following the notation in the paper.

Jet multiplicity measured for a leading-pT jet ($p_{T1}$) with $p_{T1}$ > 800 and for an azimuthal separation between the two leading jets of $170 < \Delta\Phi_{1,2} < 180^{\circ}$. The full breakdown of the uncertainties is displayed, with PU corresponding to Pileup, PREF to Trigger Prefering, PTHAT to the hard-scale (renormalization and factorization scales), MISS and FAKE to the inefficienties and background, LUMI to integrated luminosity. With JES, JER and stat. unc. following the notation in the paper.

Measured transverse momentum of the leading $p_{T}$ jet ($p_{T1}$). The full breakdown of the uncertainties is displayed, with PU corresponding to Pileup, PREF to Trigger Prefering, PTHAT to the hard-scale (renormalization and factorization scales), MISS and FAKE to the inefficienties and background, LUMI to integrated luminosity. With JES, JER and stat. unc. following the notation in the paper.

Measured transverse momentum of the subleading $p_{T}$ jet ($p_{T2}$). The full breakdown of the uncertainties is displayed, with PU corresponding to Pileup, PREF to Trigger Prefering, PTHAT to the hard-scale (renormalization and factorization scales), MISS and FAKE to the inefficienties and background, LUMI to integrated luminosity. With JES, JER and stat. unc. following the notation in the paper.

Measured transverse momentum of the third leading $p_{T}$ jet ($p_{T3}$). The full breakdown of the uncertainties is displayed, with PU corresponding to Pileup, PREF to Trigger Prefering, PTHAT to the hard-scale (renormalization and factorization scales), MISS and FAKE to the inefficienties and background, LUMI to integrated luminosity. With JES, JER and stat. unc. following the notation in the paper.

Measured transverse momentum of the fourth leading $p_{T}$ jet ($p_{T4}$). The full breakdown of the uncertainties is displayed, with PU corresponding to Pileup, PREF to Trigger Prefering, PTHAT to the hard-scale (renormalization and factorization scales), MISS and FAKE to the inefficienties and background, LUMI to integrated luminosity. With JES, JER and stat. unc. following the notation in the paper.

Jet multiplicity distribution in TUnfold binning ($N_{jets},\Delta\phi_{1,2},p_{T1}$) as indicated in the XML file provided as additional resource. The uncertainties follow the notation of Table 1.

Correlation matrix at particle level for the measured jet multiplicity in TUnfold binning ($N_{jets},\Delta\phi_{1,2},p_{T1}$) as indicated in the XML file provided as additional resource.

Jet $p_{T}$ distributions in TUnfold binning ($p_{T1},p_{T2},p_{T3},p_{T4}$) as indicated in the XML file provided as additional resource. The uncertainties follow the notation of Table 1.

Correlation matrix at particle level for the measured jet $p_{T}$ distributions in TUnfold binning ($p_{T1},p_{T2},p_{T3},p_{T4}$) as indicated in the XML file provided as additional resource.

v2 ratio of 10-20%HeAu/0-10%dAu and UC pAu/0-10%dAu

v3 ratio of 10-20%HeAu/0-10%dAu and UC pAu/0-10%dAu

Nuclear modification factor of the $\psi$(2S) shown as a function of transverse momentum

Ratio of the $\psi$(2S) over J/$\psi$ cross sections, not corrected for the branching ratio, shown as a function of transverse momentum

Double ratio of the $\psi$(2S) over J/$\psi$ cross sections in Pb--Pb and pp collisions shown as a function of transverse momentum

Observed 95% CL limits on the production cross-section for scalar up-type LQs decaying into a top quark and a neutrino or a bottom quark and an electron.

Expected 95% CL limits on the production cross-section for scalar up-type LQs decaying into a top quark and a neutrino or a bottom quark and an electron.

Observed 95% CL limits on the production cross-section for scalar down-type LQs decaying into a bottom quark and a neutrino or a top quark and a muon.

Expected 95% CL limits on the production cross-section for scalar down-type LQs decaying into a bottom quark and a neutrino or a top quark and a muon.

Observed 95% CL limits on the production cross-section for scalar down-type LQs decaying into a bottom quark and a neutrino or a top quark and an electron.

Expected 95% CL limits on the production cross-section for scalar down-type LQs decaying into a bottom quark and a neutrino or a top quark and an electron.

Observed 95% CL limits on the production cross-section for vector up-type LQs in the Yang-Mills coupling scenario decaying into a top quark and a neutrino or a bottom quark and a muon.

Expected 95% CL limits on the production cross-section for vector up-type LQs in the Yang-Mills coupling scenario decaying into a top quark and a neutrino or a bottom quark and a muon.

Observed 95% CL limits on the production cross-section for vector up-type LQs in the Yang-Mills coupling scenario decaying into a top quark and a neutrino or a bottom quark and an electron.

Expected 95% CL limits on the production cross-section for vector up-type LQs in the Yang-Mills coupling scenario decaying into a top quark and a neutrino or a bottom quark and an electron.

Observed 95% CL limits on the production cross-section for vector up-type LQs in the minimal coupling scenario decaying into a top quark and a neutrino or a bottom quark and a muon.

Expected 95% CL limits on the production cross-section for vector up-type LQs in the minimal coupling scenario decaying into a top quark and a neutrino or a bottom quark and a muon.

Observed 95% CL limits on the production cross-section for vector up-type LQs in the minimal coupling scenario decaying into a top quark and a neutrino or a bottom quark and an electron.

Expected 95% CL limits on the production cross-section for vector up-type LQs in the minimal coupling scenario decaying into a top quark and a neutrino or a bottom quark and an electron.

Product of signal acceptance and efficiency in the training region for scalar up-type LQs decaying into top quarks and neutrinos or bottom quarks and muons depending on the signal mass, $m_{LQ}$, and $\mathcal{B}(LQ_{mix}^u\rightarrow b\mu)$.

Product of signal acceptance and efficiency in the training region for scalar up-type LQs decaying into top quarks and neutrinos or bottom quarks and electrons depending on the signal mass, $m_{LQ}$, and $\mathcal{B}(LQ_{mix}^u\rightarrow be)$.

Product of signal acceptance and efficiency in the training region for scalar down-type LQs decaying into top quarks and muons or bottom quarks and neutrinos depending on the signal mass, $m_{LQ}$, and $\mathcal{B}(LQ_{mix}^d\rightarrow t\mu)$.

Product of signal acceptance and efficiency in the training region for scalar down-type LQs decaying into top quarks and electrons or bottom quarks and neutrinos depending on the signal mass, $m_{LQ}$, and $\mathcal{B}(LQ_{mix}^d\rightarrow te)$.

Product of signal acceptance and efficiency in the training region for vector LQs in the Yang-Mills coupling scenario decaying into top quarks and neutrinos or bottom quarks and muons depending on the signal mass, $m_{LQ}$, and $\mathcal{B}(vLQ_{mix}^{YM}\rightarrow b\mu)$.

Product of signal acceptance and efficiency in the training region for vector LQs in the Yang-Mills coupling scenario decaying into top quarks and neutrinos or bottom quarks and electrons depending on the signal mass, $m_{LQ}$, and $\mathcal{B}(vLQ_{mix}^{YM}\rightarrow be)$.

Product of signal acceptance and efficiency in the training region for vector LQs in the minimal coupling scenario decaying into top quarks and neutrinos or bottom quarks and muons depending on the signal mass, $m_{LQ}$, and $\mathcal{B}(vLQ_{mix}^{min}\rightarrow b\mu)$.

Product of signal acceptance and efficiency in the training region for vector LQs in the minimal coupling scenario decaying into top quarks and neutrinos or bottom quarks and electrons depending on the signal mass, $m_{LQ}$, and $\mathcal{B}(vLQ_{mix}^{min}\rightarrow be)$.

Cut-flow for the four models containing scalar LQs at a mass of $m_{LQ}=1300$ GeV and $\mathcal{B}(LQ_{mix}\rightarrow q_3\ell)=0.5$.

Cut-flow for the four models containing vector LQs at a mass of $m_{LQ}=1300$ GeV and $\mathcal{B}(LQ_{mix}\rightarrow q_3\ell)=0.5$.

$p_{\mathrm T}$-differential yield of $\mathrm{K^{*0}} + \bar{\mathrm{K^{*0}}}$ in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$7.7 GeV (Multiplicity class 60-80%).

$p_{\mathrm T}$-differential yield of $\mathrm{K^{*0}} + \bar{\mathrm{K^{*0}}}$ in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$11.5 GeV (Multiplicity class 0-10%).

$p_{\mathrm T}$-differential yield of $\mathrm{K^{*0}} + \bar{\mathrm{K^{*0}}}$ in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$11.5 GeV (Multiplicity class 10-20%).

$p_{\mathrm T}$-differential yield of $\mathrm{K^{*0}} + \bar{\mathrm{K^{*0}}}$ in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$11.5 GeV (Multiplicity class 20-30%).

$p_{\mathrm T}$-differential yield of $\mathrm{K^{*0}} + \bar{\mathrm{K^{*0}}}$ in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$11.5 GeV (Multiplicity class 30-40%).

$p_{\mathrm T}$-differential yield of $\mathrm{K^{*0}} + \bar{\mathrm{K^{*0}}}$ in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$11.5 GeV (Multiplicity class 40-60%).

$p_{\mathrm T}$-differential yield of $\mathrm{K^{*0}} + \bar{\mathrm{K^{*0}}}$ in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$11.5 GeV (Multiplicity class 60-80%).

$p_{\mathrm T}$-differential yield of $\mathrm{K^{*0}} + \bar{\mathrm{K^{*0}}}$ in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$14.5 GeV (Multiplicity class 0-10%).

$p_{\mathrm T}$-differential yield of $\mathrm{K^{*0}} + \bar{\mathrm{K^{*0}}}$ in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$14.5 GeV (Multiplicity class 10-20%).

$p_{\mathrm T}$-differential yield of $\mathrm{K^{*0}} + \bar{\mathrm{K^{*0}}}$ in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$14.5 GeV (Multiplicity class 20-30%).

$p_{\mathrm T}$-differential yield of $\mathrm{K^{*0}} + \bar{\mathrm{K^{*0}}}$ in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$14.5 GeV (Multiplicity class 30-40%).

$p_{\mathrm T}$-differential yield of $\mathrm{K^{*0}} + \bar{\mathrm{K^{*0}}}$ in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$14.5 GeV (Multiplicity class 40-60%).

$p_{\mathrm T}$-differential yield of $\mathrm{K^{*0}} + \bar{\mathrm{K^{*0}}}$ in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$14.5 GeV (Multiplicity class 60-80%).

$p_{\mathrm T}$-differential yield of $\mathrm{K^{*0}} + \bar{\mathrm{K^{*0}}}$ in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$19.6 GeV (Multiplicity class 0-10%).

$p_{\mathrm T}$-differential yield of $\mathrm{K^{*0}} + \bar{\mathrm{K^{*0}}}$ in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$19.6 GeV (Multiplicity class 10-20%).

$p_{\mathrm T}$-differential yield of $\mathrm{K^{*0}} + \bar{\mathrm{K^{*0}}}$ in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$19.6 GeV (Multiplicity class 20-30%).

$p_{\mathrm T}$-differential yield of $\mathrm{K^{*0}} + \bar{\mathrm{K^{*0}}}$ in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$19.6 GeV (Multiplicity class 30-40%).

$p_{\mathrm T}$-differential yield of $\mathrm{K^{*0}} + \bar{\mathrm{K^{*0}}}$ in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$19.6 GeV (Multiplicity class 40-60%).

$p_{\mathrm T}$-differential yield of $\mathrm{K^{*0}} + \bar{\mathrm{K^{*0}}}$ in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$19.6 GeV (Multiplicity class 60-80%).

$p_{\mathrm T}$-differential yield of $\mathrm{K^{*0}} + \bar{\mathrm{K^{*0}}}$ in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$27 GeV (Multiplicity class 0-10%).

$p_{\mathrm T}$-differential yield of $\mathrm{K^{*0}} + \bar{\mathrm{K^{*0}}}$ in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$27 GeV (Multiplicity class 10-20%).

$p_{\mathrm T}$-differential yield of $\mathrm{K^{*0}} + \bar{\mathrm{K^{*0}}}$ in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$27 GeV (Multiplicity class 20-30%).

$p_{\mathrm T}$-differential yield of $\mathrm{K^{*0}} + \bar{\mathrm{K^{*0}}}$ in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$27 GeV (Multiplicity class 30-40%).

$p_{\mathrm T}$-differential yield of $\mathrm{K^{*0}} + \bar{\mathrm{K^{*0}}}$ in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$27 GeV (Multiplicity class 40-60%).

$p_{\mathrm T}$-differential yield of $\mathrm{K^{*0}} + \bar{\mathrm{K^{*0}}}$ in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$27 GeV (Multiplicity class 60-80%).

$p_{\mathrm T}$-differential yield of $\mathrm{K^{*0}} + \bar{\mathrm{K^{*0}}}$ in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$39 GeV (Multiplicity class 0-10%).

$p_{\mathrm T}$-differential yield of $\mathrm{K^{*0}} + \bar{\mathrm{K^{*0}}}$ in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$39 GeV (Multiplicity class 10-20%).

$p_{\mathrm T}$-differential yield of $\mathrm{K^{*0}} + \bar{\mathrm{K^{*0}}}$ in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$39 GeV (Multiplicity class 20-30%).

$p_{\mathrm T}$-differential yield of $\mathrm{K^{*0}} + \bar{\mathrm{K^{*0}}}$ in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$39 GeV (Multiplicity class 30-40%).

$p_{\mathrm T}$-differential yield of $\mathrm{K^{*0}} + \bar{\mathrm{K^{*0}}}$ in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$39 GeV (Multiplicity class 40-60%).

$p_{\mathrm T}$-differential yield of $\mathrm{K^{*0}} + \bar{\mathrm{K^{*0}}}$ in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$39 GeV (Multiplicity class 60-80%).

$p_{\mathrm T}$- integrated yield of $\mathrm{K^{*0}} + \bar{\mathrm{K^{*0}}}$ vs. < Npart > in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$7.7 GeV. Total systematic error is the quadrature sum of the correlated and uncorrelated systematic errors

$p_{\mathrm T}$- integrated yield of $\mathrm{K^{*0}} + \bar{\mathrm{K^{*0}}}$ vs. < Npart > in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$11.5 GeV. Total systematic error is the quadrature sum of the correlated and uncorrelated systematic errors

$p_{\mathrm T}$- integrated yield of $\mathrm{K^{*0}} + \bar{\mathrm{K^{*0}}}$ vs. < Npart > in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$14.5 GeV. Total systematic error is the quadrature sum of the correlated and uncorrelated systematic errors

$p_{\mathrm T}$- integrated yield of $\mathrm{K^{*0}} + \bar{\mathrm{K^{*0}}}$ vs. < Npart > in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$19.6 GeV. Total systematic error is the quadrature sum of the correlated and uncorrelated systematic errors

$p_{\mathrm T}$- integrated yield of $\mathrm{K^{*0}} + \bar{\mathrm{K^{*0}}}$ vs. < Npart > in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$27 GeV. Total systematic error is the quadrature sum of the correlated and uncorrelated systematic errors

$p_{\mathrm T}$- integrated yield of $\mathrm{K^{*0}} + \bar{\mathrm{K^{*0}}}$ vs. < Npart > in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$39 GeV. Total systematic error is the quadrature sum of the correlated and uncorrelated systematic errors

<$p_{\mathrm T}$> of $\mathrm{K^{*0}} + \bar{\mathrm{K^{*0}}}$ vs. < Npart > in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$7.7 GeV. Total systematic error is the quadrature sum of the correlated and uncorrelated systematic errors

<$p_{\mathrm T}$> of $\mathrm{K^{*0}} + \bar{\mathrm{K^{*0}}}$ vs. < Npart > in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$11.5 GeV. Total systematic error is the quadrature sum of the correlated and uncorrelated systematic errors

<$p_{\mathrm T}$> of $\mathrm{K^{*0}} + \bar{\mathrm{K^{*0}}}$ vs. < Npart > in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$14.5 GeV. Total systematic error is the quadrature sum of the correlated and uncorrelated systematic errors

<$p_{\mathrm T}$> of $\mathrm{K^{*0}} + \bar{\mathrm{K^{*0}}}$ vs. < Npart > in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$19.6 GeV. Total systematic error is the quadrature sum of the correlated and uncorrelated systematic errors

<$p_{\mathrm T}$> of $\mathrm{K^{*0}} + \bar{\mathrm{K^{*0}}}$ vs. < Npart > in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$27 GeV. Total systematic error is the quadrature sum of the correlated and uncorrelated systematic errors

<$p_{\mathrm T}$> of $\mathrm{K^{*0}} + \bar{\mathrm{K^{*0}}}$ vs. < Npart > in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$39 GeV. Total systematic error is the quadrature sum of the correlated and uncorrelated systematic errors

$\frac{\mathrm{K^{*0}} + \bar{\mathrm{K^{*0}}}}{K^{+} + K^{-}}$ vs. < Npart > in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$7.7 GeV. Total systematic error is the quadrature sum of the correlated and uncorrelated systematic errors

$\frac{\mathrm{K^{*0}} + \bar{\mathrm{K^{*0}}}}{K^{+} + K^{-}}$ vs. < Npart > in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$11.5 GeV. Total systematic error is the quadrature sum of the correlated and uncorrelated systematic errors

$\frac{\mathrm{K^{*0}} + \bar{\mathrm{K^{*0}}}}{K^{+} + K^{-}}$ vs. < Npart > in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$14.5 GeV. Total systematic error is the quadrature sum of the correlated and uncorrelated systematic errors

$\frac{\mathrm{K^{*0}} + \bar{\mathrm{K^{*0}}}}{K^{+} + K^{-}}$ vs. < Npart > in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$19.6 GeV. Total systematic error is the quadrature sum of the correlated and uncorrelated systematic errors

$\frac{\mathrm{K^{*0}} + \bar{\mathrm{K^{*0}}}}{K^{+} + K^{-}}$ vs. < Npart > in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$27 GeV. Total systematic error is the quadrature sum of the correlated and uncorrelated systematic errors

$\frac{\mathrm{K^{*0}} + \bar{\mathrm{K^{*0}}}}{K^{+} + K^{-}}$ vs. < Npart > in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$39 GeV. Total systematic error is the quadrature sum of the correlated and uncorrelated systematic errors

$\frac{\mathrm{K^{*0}} + \bar{\mathrm{K^{*0}}}}{K^{+} + K^{-}}$ vs. $<(dN_{ch}/dy)^{1/3}>$ in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$7.7 GeV. Total systematic error is the quadrature sum of the correlated and uncorrelated systematic errors

$\frac{\mathrm{K^{*0}} + \bar{\mathrm{K^{*0}}}}{K^{+} + K^{-}}$ vs. $<(dN_{ch}/dy)^{1/3}>$ in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~11.5 GeV. Total systematic error is the quadrature sum of the correlated and uncorrelated systematic errors

$\frac{\mathrm{K^{*0}} + \bar{\mathrm{K^{*0}}}}{K^{+} + K^{-}}$ vs. $<(dN_{ch}/dy)^{1/3}>$ in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$14.5GeV. Total systematic error is the quadrature sum of the correlated and uncorrelated systematic errors

$\frac{\mathrm{K^{*0}} + \bar{\mathrm{K^{*0}}}}{K^{+} + K^{-}}$ vs. $<(dN_{ch}/dy)^{1/3}>$ in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$19.6 GeV. Total systematic error is the quadrature sum of the correlated and uncorrelated systematic errors

$\frac{\mathrm{K^{*0}} + \bar{\mathrm{K^{*0}}}}{K^{+} + K^{-}}$ vs. $<(dN_{ch}/dy)^{1/3}>$ in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$27 GeV. Total systematic error is the quadrature sum of the correlated and uncorrelated systematic errors

$\frac{\mathrm{K^{*0}} + \bar{\mathrm{K^{*0}}}}{K^{+} + K^{-}}$ vs. $<(dN_{ch}/dy)^{1/3}>$ in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$39 GeV. Total systematic error is the quadrature sum of the correlated and uncorrelated systematic errors

$\frac{2\phi}{K^{+} + K^{-}}$ vs. < Npart > in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$7.7 GeV

$\frac{2\phi}{K^{+} + K^{-}}$ vs. < Npart > in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$11.5 GeV

$\frac{2\phi}{K^{+} + K^{-}}$ vs. < Npart > in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$19.6 GeV

$\frac{2\phi}{K^{+} + K^{-}}$ vs. < Npart > in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$27 GeV

$\frac{2\phi}{K^{+} + K^{-}}$ vs. < Npart > in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$39 GeV

lower limit of hadronic phase lifetime vs. < Npart > in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$7.7 GeV

lower limit of hadronic phase lifetime vs. < Npart > in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$11.5 GeV

lower limit of hadronic phase lifetime vs. < Npart > in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$14.5 GeV

lower limit of hadronic phase lifetime vs. < Npart > in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$19.6 GeV

lower limit of hadronic phase lifetime vs. < Npart > in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$27 GeV

lower limit of hadronic phase lifetime vs. < Npart > in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$39 GeV

lower limit of hadronic phase lifetime vs. < Npart > in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$62.4 GeV

lower limit of hadronic phase lifetime vs. < Npart > in AuAu collisions at $\sqrt{s_{\mathrm{NN}}}~=~$200 GeV

Results of applying the BH algorithm to the mass spectra in the leading photon category, using the fitted background estimations from the initial step

Results of applying the BH algorithm to the mass spectra in the leading electron category, using the fitted background estimations from the initial step

Results of applying the BH algorithm to the mass spectra in the leading muon category, using the fitted background estimations from the initial step

Results of applying the BH algorithm to the mass spectra in the leading small-R jet category, using the fitted background estimations from the initial step

Results of applying the BH algorithm to the mass spectra in the leading bjet category, using the fitted background estimations from the initial step

Results of applying the BH algorithm to the mass spectra in the leading large-R jet category, using the fitted background estimations from the initial step

Results of applying the BH algorithm to the mass spectra in the leading photon category, using the fitted background estimations from the initial step

Results of applying the BH algorithm to the mass spectra in the leading electron category, using the fitted background estimations from the initial step

Results of applying the BH algorithm to the mass spectra in the leading muon category, using the fitted background estimations from the initial step

Results of applying the BH algorithm to the mass spectra in the inclusive category, using the fitted background estimations from the initial step

Results of applying the BH algorithm to the mass spectra in the inclusive category, using the fitted background estimations from the initial step

Upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signal with a relative width value of 3% as a function of mass in the leading small-R jet category

Upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signal with a relative width value of 3% as a function of mass in the leading bjet category

Upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signal with a relative width value of 3% as a function of mass in the leading large-R jet category

Upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signal with a relative width value of 3% as a function of mass in the leading photon category

Upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signal with a relative width value of 3% as a function of mass in the leading electron category

Upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signal with a relative width value of 3% as a function of mass in the leading muon category

Upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signal with a relative width value of 3% as a function of mass in the leading small-R jet category

Upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signal with a relative width value of 3% as a function of mass in the leading bjet category

Upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signal with a relative width value of 3% as a function of mass in the leading large-R jet category

Upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signal with a relative width value of 3% as a function of mass in the leading photon category

Upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signal with a relative width value of 3% as a function of mass in the leading electron category

Upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signal with a relative width value of 3% as a function of mass in the leading muon category

Upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signal with a relative width value of 3% as a function of mass in the inclusive category

Upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signal with a relative width value of 3% as a function of mass in the inclusive category

Comparison of observed upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signals with relative width values as a function of mass in the leading small-R jet category

Comparison of observed upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signals with relative width values as a function of mass in the leading bjet category

Comparison of observed upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signals with relative width values as a function of mass in the leading large-R jet category

Comparison of observed upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signals with relative width values as a function of mass in the leading photon category

Comparison of observed upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signals with relative width values as a function of mass in the leading electron category

Comparison of observed upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signals with relative width values as a function of mass in the leading muon category

Comparison of observed upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signals with relative width values as a function of mass in the leading small-R jet category

Comparison of observed upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signals with relative width values as a function of mass in the leading bjet category

Comparison of observed upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signals with relative width values as a function of mass in the leading large-R jet category

Comparison of observed upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signals with relative width values as a function of mass in the leading photon category

Comparison of observed upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signals with relative width values as a function of mass in the leading electron category

Comparison of observed upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signals with relative width values as a function of mass in the leading muon category

Comparison of observed upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signals with relative width values as a function of mass in the inclusive category

Comparison of observed upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signals with relative width values as a function of mass in the inclusive category

Acceptance times efficiency in an HVT model as a function of mass in the leading large-R jet category

Upper limits at 95% CL on the cross section times the branching fraction($W^{\prime} \to ZW$) for the HVT signal as functions of mass($m_{ZX}$) in the leading large-R jet category.The full(dashed) red curves correspond to the theoretical predictions of HVT model A(B)

Comparison of the identification efficiencies using standard and merged-ee reconstruction as a function of true PT(Z)

Background rejection factor as a function of signal efficiency. The red curve shows the BDT performance whereas the blue curve corresponds to that of a cut-based analysis relying only on the jet energyfraction deposited in the EM calorimeter

BH p-values of the 100 pseudo-experiments as a function of in the leading small-R jet category for an injected Gaussian-shaped signal with a relative width value of 3%. The fractions of the pseudo-experiments that have the correctly identified interval and BH p-values below the threshold of 0.01 are indicated. The background is derived by the background-only fit in the full fitting range.

BH p-values of the 100 pseudo-experiments as a function of in the leading small-R jet category for an injected Gaussian-shaped signal with a relative width value of 3%. The fractions of the pseudo-experiments that have the correctly identified interval and BH p-values below the threshold of 0.01 are indicated. The background is derived by the background-only fit in the range excluding the BH interval.

Fractions of pseudo-experiments in which the detected BH interval agrees with the injected mass point and the BH p-value is below 0.01 as a function of mass in the leading small-R jet category for Gaussian-shaped signal with a relative width of 3%.

Fractions of pseudo-experiments in which the detected BH interval agrees with the injected mass point and the BH p-value is below 0.01 as a function of mass in the leading small-R jet category for Gaussian-shaped signal with a relative width of 3%.

Distribution of exclusion upper limits on signal event yields at 95% CL from 1000 pseudo-experiments for Gaussian-shaped signals with relative width values of 3% at the low boundary of the limit-sensitive mass range for the ZX spectrum of the leading small-R jet category. The vertical line corresponds to the expected nominal exclusion limit at 95% CL.

Distribution of exclusion upper limits on signal event yields at 95% CL from 1000 pseudo-experiments for Gaussian-shaped signals with relative width values of 3% at the high boundary of the limit-sensitive mass range for the ZX spectrum of the leading small-R jet category. The vertical line corresponds to the expected nominal exclusion limit at 95% CL.

Distribution of exclusion upper limits on signal event yields at 95% CL from 1000 pseudo-experiments for Gaussian-shaped signals with relative width values of 5% at the low boundary of the limit-sensitive mass range for the ZX spectrum of the leading small-R jet category. The vertical line corresponds to the expected nominal exclusion limit at 95% CL.

Distribution of exclusion upper limits on signal event yields at 95% CL from 1000 pseudo-experiments for Gaussian-shaped signals with relative width values of 5% at the high boundary of the limit-sensitive mass range for the ZX spectrum of the leading small-R jet category. The vertical line corresponds to the expected nominal exclusion limit at 95% CL.

Distribution of exclusion upper limits on signal event yields at 95% CL from 1000 pseudo-experiments for Gaussian-shaped signals with relative width values of 10% at the low boundary of the limit-sensitive mass range for the ZX spectrum of the leading small-R jet category. The vertical line corresponds to the expected nominal exclusion limit at 95% CL.

Distribution of exclusion upper limits on signal event yields at 95% CL from 1000 pseudo-experiments for Gaussian-shaped signals with relative width values of 10% at the high boundary of the limit-sensitive mass range for the ZX spectrum of the leading small-R jet category. The vertical line corresponds to the expected nominal exclusion limit at 95% CL.

Data yields of the six event categories in the $Z\to e^+e^-$ and $\mu^+\mu^-$ decay channels. The merged-$e^+e^-$ events are included in the $e^+e^-$ channel, increasing the event yield, mainly in the leading large-$R$-jet category, by 0.6 %.

A list of mass spectra, event categories and their corresponding fit ranges, functional forms, numbers of free parameters and global $\chi^2$ $p$-values from background-only fits. The fit range values are rounded to the nearest 5 GeV. Here $f_1(x)=p_0\left(\mathrm{e}^{-p_1x}+p_2\mathrm{e}^{-(p_1+p_3)x}+p_4\mathrm{e}^{-(p_1+p_3+p_5)x}+\cdots\right)$ and $f_2(x)=p_0(1-x)^{p_1}x^{p_2+p_3\ln\!x+p_4\ln^2\!x+\cdots}$

A list of mass spectra, event categories and their corresponding signal-sensitive mass ranges. The initial BH $p$-value is obtained by using the background derived from the background-only fit in the full fit range, whereas the new BH $p$-value uses the background derived from the background-only fit in the range excluding the initial BH interval.

A list of mass spectra, event categories, relative width values of Gaussian-shaped signals and limit-sensitive mass ranges and fractions, corresponding to the mass values in the previous column, of pseudo-experiments having exclusion upper limits higher than the nominal exclusion limit at 95% CL

Cutflow of HVT model $A$ signals ($W^\prime \to ZW \to \ell\ell qq$) with $m_{W^\prime} = 1$ TeV and $m_{W^\prime} = 4$ TeV based on MC simulations.

Acceptance times efficiency ($\mathcal{A} \times \epsilon$) values in % in the dominant event category for $p^Z_{\mathrm{T}} > 100$ GeV in the $Z \to \ell^{+}\ell^{-}$ decay channel.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[110,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[110,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[120,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[120,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[130,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[130,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[100,105)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[100,105)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[105,110)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[105,110)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[110,115)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[110,115)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[115,120)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[115,120)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[120,125)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[120,125)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[125,130)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[125,130)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[130,140)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[130,140)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[140,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[140,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[100,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[100,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[110,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[110,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[120,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[120,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[130,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[130,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[100,105)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[100,105)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[105,110)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[105,110)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[110,115)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[110,115)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[115,120)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[115,120)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[120,125)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[120,125)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[125,130)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[125,130)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[130,140)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[130,140)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[140,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[140,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

Cutflow table for the slepton signal sample with $m(\tilde{\ell},\tilde{\chi}_1^0) = (100,70)$ GeV, in the SR-0J $m_{\mathrm{T2}}^{100} \in [100,\infty)$ region. The yields include the process cross section and are weighted to the 139 fb$^{-1}$ luminosity. 246000 events were generated for the sample.

Cutflow table for the slepton signal sample with $m(\tilde{\ell},\tilde{\chi}_1^0) = (100,70)$ GeV, in the SR-1J $m_{\mathrm{T2}}^{100} \in [100,\infty)$ region. The yields include the process cross section and are weighted to the 139 fb$^{-1}$ luminosity. 246000 events were generated for the sample.

Observed and expected exclusion limits on SUSY simplified models, with observed upper limits on signal cross-section (fb) overlaid, for slepton-pair production in the $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ plane. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP for $\tilde{\mu}_{\textup{R}}$ and by the ATLAS experiment in previous searches are also shown.

Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the (a) $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\ell})-\Delta m(\tilde{\ell},\tilde{\chi}_1^0)$ planes. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP for $\tilde{\mu}_{\textup{R}}$ and by the ATLAS experiment in previous searches are also shown.

Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the (a) $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\ell})-\Delta m(\tilde{\ell},\tilde{\chi}_1^0)$ planes. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP for $\tilde{\mu}_{\textup{R}}$ and by the ATLAS experiment in previous searches are also shown.

Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the (a) $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\ell})-\Delta m(\tilde{\ell},\tilde{\chi}_1^0)$ planes. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP for $\tilde{\mu}_{\textup{R}}$ and by the ATLAS experiment in previous searches are also shown.

Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the (a) $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\ell})-\Delta m(\tilde{\ell},\tilde{\chi}_1^0)$ planes. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP for $\tilde{\mu}_{\textup{R}}$ and by the ATLAS experiment in previous searches are also shown.

Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the (a) $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\ell})-\Delta m(\tilde{\ell},\tilde{\chi}_1^0)$ planes. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP for $\tilde{\mu}_{\textup{R}}$ and by the ATLAS experiment in previous searches are also shown.

Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the (a) $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\ell})-\Delta m(\tilde{\ell},\tilde{\chi}_1^0)$ planes. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP for $\tilde{\mu}_{\textup{R}}$ and by the ATLAS experiment in previous searches are also shown.

Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the (a) $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\ell})-\Delta m(\tilde{\ell},\tilde{\chi}_1^0)$ planes. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP for $\tilde{\mu}_{\textup{R}}$ and by the ATLAS experiment in previous searches are also shown.

Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the (a) $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\ell})-\Delta m(\tilde{\ell},\tilde{\chi}_1^0)$ planes. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP for $\tilde{\mu}_{\textup{R}}$ and by the ATLAS experiment in previous searches are also shown.

Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the (a) $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\ell})-\Delta m(\tilde{\ell},\tilde{\chi}_1^0)$ planes. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP for $\tilde{\mu}_{\textup{R}}$ and by the ATLAS experiment in previous searches are also shown.

Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the (a) $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\ell})-\Delta m(\tilde{\ell},\tilde{\chi}_1^0)$ planes. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP for $\tilde{\mu}_{\textup{R}}$ and by the ATLAS experiment in previous searches are also shown.

Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the (a) $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\ell})-\Delta m(\tilde{\ell},\tilde{\chi}_1^0)$ planes. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP for $\tilde{\mu}_{\textup{R}}$ and by the ATLAS experiment in previous searches are also shown.

Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the (a) $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\ell})-\Delta m(\tilde{\ell},\tilde{\chi}_1^0)$ planes. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP for $\tilde{\mu}_{\textup{R}}$ and by the ATLAS experiment in previous searches are also shown.

Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.

Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.

Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.

Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.

Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.

Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.

Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.

Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.

Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.

Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.

Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.

Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.

Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.

Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.

Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.

Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.

Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.

Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.

Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.

Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.

Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.

Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.

Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.

Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.

Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ plane. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The red contour shows the exclusion limits obtained using both the SR-0J and SR-1J region, as presented in Figure 6. The blue and green contours correspond to the result obtained considering only SR-0J and SR-1J region respectively. All limits are computed at 95% CL. The observed limits obtained by the ATLAS experiment in previous searches are also shown.

Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ plane. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The red contour shows the exclusion limits obtained using both the SR-0J and SR-1J region, as presented in Figure 6. The blue and green contours correspond to the result obtained considering only SR-0J and SR-1J region respectively. All limits are computed at 95% CL. The observed limits obtained by the ATLAS experiment in previous searches are also shown.

Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ plane. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The red contour shows the exclusion limits obtained using both the SR-0J and SR-1J region, as presented in Figure 6. The blue and green contours correspond to the result obtained considering only SR-0J and SR-1J region respectively. All limits are computed at 95% CL. The observed limits obtained by the ATLAS experiment in previous searches are also shown.

Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ plane. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The red contour shows the exclusion limits obtained using both the SR-0J and SR-1J region, as presented in Figure 6. The blue and green contours correspond to the result obtained considering only SR-0J and SR-1J region respectively. All limits are computed at 95% CL. The observed limits obtained by the ATLAS experiment in previous searches are also shown.

The upper panel shows the observed number of events in each of the binned SRs defined in Table 3, together with the expected SM backgrounds obtained after applying the efficiency correction method to compute the number of expected FSB events. `Others' include the non-dominant background sources, e.g. $t \bar{t}$+$V$, Higgs boson and Drell--Yan events. The uncertainty band includes systematic and statistical errors from all sources. The distributions of two signal points with mass splittings $\Delta m(\tilde{\ell},\tilde{\chi}_1^0) = m(\tilde{\ell})-m(\tilde{\chi}_1^0) = 30$ GeV and $\Delta m(\tilde{\ell},\tilde{\chi}_1^0) = m(\tilde{\ell})-m(\tilde{\chi}_1^0) = 50$ GeV are overlaid. The lower panel shows the significance as defined in Ref. [115].

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR$^{\text{-DF BDT-signal}\in(0.81,1]}_{\text{-SF BDT-signal}\in(0.77,1]}$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR$^{\text{-DF BDT-signal}\in(0.81,1]}_{\text{-SF BDT-signal}\in(0.77,1]}$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.81,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.81,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.82,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.82,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.83,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.83,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.84,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.84,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.85,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.85,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.81,0.8125]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.81,0.8125]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.8125,0.815]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.8125,0.815]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.815,0.8175]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.815,0.8175]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.8175,0.82]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.8175,0.82]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.82,0.8225]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.82,0.8225]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.8225,0.825]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.8225,0.825]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.825,0.8275]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.825,0.8275]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.8275,0.83]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.8275,0.83]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.83,0.8325]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.83,0.8325]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.8325,0.835]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.8325,0.835]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.835,0.8375]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.835,0.8375]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.8375,0.84]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.8375,0.84]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.84,0.845]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.84,0.845]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.845,0.85]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.845,0.85]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.85,0.86]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.85,0.86]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.86,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.86,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.77,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.77,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.78,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.78,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.