Upper limits at 95% CL on $\sigma$B(pp→X→Y(bb)H) for combination as a function of m$_Y$.

Expected upper limits at 95% CL on the X → HH cross section as a function of mX from the combination of the three channels bbγγ, bbττ, and bbbb for an integrated luminosity of 3000 fb−1 with different assumptions on the systematic uncertainties.

Expected upper limits on the X → YH cross section times B(Y → bb) for mX ≤ 1000 GeV at 95 % CL as a function of m$_X$ and m$_Y$ from the combination of all considered channels projected to an integrated luminosity of 3000 fb$^{-1}$. Systematic uncertainties according to the ”S2” scenario are assumed.

Expected and observed 95% CL upper limits on $|V_\mathrm{N}|^2$ as a function of $m_\mathrm{N}$ for the mixing scenario ($r_e$, $r_\mu$, $r_\tau$) = (0.33, 0.33, 0.33) and in the Majorana scenario.

Expected and observed 95% CL upper limits on $|V_\mathrm{N}|^2$ as a function of $m_\mathrm{N}$ for the mixing scenario ($r_e$, $r_\mu$, $r_\tau$) = (0.0, 1.0, 0.0) and in the Dirac-like scenario.

Expected and observed 95% CL upper limits on $|V_\mathrm{N}|^2$ as a function of $m_\mathrm{N}$ for the mixing scenario ($r_e$, $r_\mu$, $r_\tau$) = (0.0, 0.5, 0.5) and in the Dirac-like scenario.

Expected and observed 95% CL upper limits on $|V_\mathrm{N}|^2$ as a function of $m_\mathrm{N}$ for the mixing scenario ($r_e$, $r_\mu$, $r_\tau$) = (0.5, 0.5, 0.0) and in the Dirac-like scenario.

Expected and observed 95% CL upper limits on $|V_\mathrm{N}|^2$ as a function of $m_\mathrm{N}$ for the mixing scenario ($r_e$, $r_\mu$, $r_\tau$) = (0.33, 0.33, 0.33) and in the Dirac-like scenario.

Observed 95% CL lower limits on $c\tau_\mathrm{N}$ as functions of the mixing ratios ($r_e$, $r_\mu$, $r_\tau$) for a fixed N mass of 1.0 GeV in the Majorana scenario.

Observed 95% CL lower limits on $c\tau_\mathrm{N}$ as functions of the mixing ratios ($r_e$, $r_\mu$, $r_\tau$) for a fixed N mass of 1.5 GeV in the Majorana scenario.

Observed 95% CL lower limits on $c\tau_\mathrm{N}$ as functions of the mixing ratios ($r_e$, $r_\mu$, $r_\tau$) for a fixed N mass of 2.0 GeV in the Majorana scenario.

Observed 95% CL lower limits on $c\tau_\mathrm{N}$ as functions of the mixing ratios ($r_e$, $r_\mu$, $r_\tau$) for a fixed N mass of 1.0 GeV in the Dirac-like scenario.

Observed 95% CL lower limits on $c\tau_\mathrm{N}$ as functions of the mixing ratios ($r_e$, $r_\mu$, $r_\tau$) for a fixed N mass of 1.5 GeV in the Dirac-like scenario.

Observed 95% CL lower limits on $c\tau_\mathrm{N}$ as functions of the mixing ratios ($r_e$, $r_\mu$, $r_\tau$) for a fixed N mass of 2.0 GeV in the Dirac-like scenario.

Reconstruction level differential cross section spectla, obtained for the central acceptance, $|\eta| < 3$, for events with Pomeron-Proton ($\mathrm{I\!P}\mathrm{p} + \gamma \mathrm{p}$) topology compared to the to the EPOS-LHC predictions, broken down into the non-diffractive (ND), central diffractive (CD), single diffractive (SD) and double diffractive (DD) components. Forward Rapidity Gap definition: $|\eta| < 2.5$: $p_{T}^{track} < 200$ MeV and $\sum \limits_{bin} E^{PF} < 6$ GeV $|\eta| \in [2.5,3.0]$: $\sum \limits_{bin} E_{neutral}^{PF} < 13.4$ GeV

The number of high purity tracksin the first $\eta$ bin after a gap of $4.5 \leq \Delta\eta^F < 5.0$ for events with the Pomeron-Proton ($\mathrm{I\!P}\mathrm{p} + \gamma \mathrm{p}$) topology Forward Rapidity Gap definition: $|\eta| < 2.5$: $p_{T}^{track} < 200$ MeV and $\sum \limits_{bin} E^{PF} < 6$ GeV $|\eta| \in [2.5,3.0]$: $\sum \limits_{bin} E_{neutral}^{PF} < 13.4$ GeV

The transeverse momentum of high purity tracksin the first $\eta$ bin after a gap of $4.5 \leq \Delta\eta^F < 5.0$ for events with the Pomeron-Proton ($\mathrm{I\!P}\mathrm{p} + \gamma \mathrm{p}$) topology Forward Rapidity Gap definition: $|\eta| < 2.5$: $p_{T}^{track} < 200$ MeV and $\sum \limits_{bin} E^{PF} < 6$ GeV $|\eta| \in [2.5,3.0]$: $\sum \limits_{bin} E_{neutral}^{PF} < 13.4$ GeV

The total energy of all Particle Flow candidatesin the first $\eta$ bin after a gap of $4.5 \leq \Delta\eta^F < 5.0$ for events with the Pomeron-Proton ($\mathrm{I\!P}\mathrm{p} + \gamma \mathrm{p}$) topology Forward Rapidity Gap definition: $|\eta| < 2.5$: $p_{T}^{track} < 200$ MeV and $\sum \limits_{bin} E^{PF} < 6$ GeV $|\eta| \in [2.5,3.0]$: $\sum \limits_{bin} E_{neutral}^{PF} < 13.4$ GeV

Unfolded diffraction enhanced differential cross section for events with Pomeron-Lead ($\mathrm{I\!P}\mathrm{Pb}$) topology, defined on the region $|\eta| < 5.2$, compared to hadron level predictions of the MC generators. The data are corrected for the contribution from events with undetectable energy in the HF calorimeter adjacent to the rapidity gap. The corrections are obtained using the EPOS-LHC MC sample. Forward Rapidity Gap definition: $|\eta| < 2.5$: $p_{T}^{track} < 200$ MeV and $\sum \limits_{bin} E^{PF} < 6$ GeV $|\eta| \in [2.5,3.0]$: $\sum \limits_{bin} E_{neutral}^{PF} < 13.4$ GeV $|\eta| > 3.0$: No particles

Unfolded diffraction enhanced differential cross section for events with Pomeron-Proton ($\mathrm{I\!P}\mathrm{p} + \gamma \mathrm{p}$) topology, defined on the region $|\eta| < 5.2$, compared to hadron level predictions of the MC generators. The data are corrected for the contribution from events with undetectable energy in the HF calorimeter adjacent to the rapidity gap. The corrections are obtained using the EPOS-LHC MC sample. Forward Rapidity Gap definition: $|\eta| < 2.5$: $p_{T}^{track} < 200$ MeV and $\sum \limits_{bin} E^{PF} < 6$ GeV $|\eta| \in [2.5,3.0]$: $\sum \limits_{bin} E_{neutral}^{PF} < 13.4$ GeV $|\eta| > 3.0$: No particles

Unfolded diffractive enhanced differential cross section spectla for events with Pomeron-Lead ($\mathrm{I\!P}\mathrm{Pb}$) topology, compared to the to the hadron-level EPOS-LHC predictions, broken down into the non-diffractive (ND), central diffractive (CD), single diffractive (SD) and double diffractive (DD) components. Forward Rapidity Gap definition: $|\eta| < 2.5$: $p_{T}^{track} < 200$ MeV and $\sum \limits_{bin} E^{PF} < 6$ GeV $|\eta| \in [2.5,3.0]$: $\sum \limits_{bin} E_{neutral}^{PF} < 13.4$ GeV $|\eta| > 3.0$: No particles

Unfolded diffractive enhanced differential cross section spectla for events with Pomeron-Proton ($\mathrm{I\!P}\mathrm{p} + \gamma \mathrm{p}$) topology, compared to the to the hadron-level EPOS-LHC predictions, broken down into the non-diffractive (ND), central diffractive (CD), single diffractive (SD) and double diffractive (DD) components. Forward Rapidity Gap definition: $|\eta| < 2.5$: $p_{T}^{track} < 200$ MeV and $\sum \limits_{bin} E^{PF} < 6$ GeV $|\eta| \in [2.5,3.0]$: $\sum \limits_{bin} E_{neutral}^{PF} < 13.4$ GeV $|\eta| > 3.0$: No particles

Unfolded diffractive enhanced differential cross section spectla for events with Pomeron-Lead ($\mathrm{I\!P}\mathrm{Pb}$) topology, compared to the to the hadron-level QGSJET II predictions, broken down into the non-diffractive (ND), central diffractive (CD), single diffractive (SD) and double diffractive (DD) components. Forward Rapidity Gap definition: $|\eta| < 2.5$: $p_{T}^{track} < 200$ MeV and $\sum \limits_{bin} E^{PF} < 6$ GeV $|\eta| \in [2.5,3.0]$: $\sum \limits_{bin} E_{neutral}^{PF} < 13.4$ GeV $|\eta| > 3.0$: No particles

Unfolded diffractive enhanced differential cross section spectla for events with Pomeron-Proton ($\mathrm{I\!P}\mathrm{p} + \gamma \mathrm{p}$) topology, compared to the to the hadron-level QGSJET II predictions, broken down into the non-diffractive (ND), central diffractive (CD), single diffractive (SD) and double diffractive (DD) components. Forward Rapidity Gap definition: $|\eta| < 2.5$: $p_{T}^{track} < 200$ MeV and $\sum \limits_{bin} E^{PF} < 6$ GeV $|\eta| \in [2.5,3.0]$: $\sum \limits_{bin} E_{neutral}^{PF} < 13.4$ GeV $|\eta| > 3.0$: No particles

Reconstruction level diffraction enhanced differential cross section spectrum for Pomeron-Proton ($\mathrm{I\!P}\mathrm{p} + \gamma \mathrm{p}$) topology corrected for the contribution from events with undetectable energy in the HF calorimeter adjacent to the rapidity gap, compared with the spectrum obtained with events satisfying the ZDC veto requirement $E_{ZDC−} < 1 \mathrm{~TeV}$ which selects only the events without lead nuclear break up (without correction for HF undetectable energy). Forward Rapidity Gap definition: $|\eta| < 2.5$: $p_{T}^{track} < 200$ MeV and $\sum \limits_{bin} E^{PF} < 6$ GeV $|\eta| \in [2.5,3.0]$: $\sum \limits_{bin} E_{neutral}^{PF} < 13.4$ GeV $|\eta| > 3.0$: No particles

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.

Differential cross section times dimuon branching fraction of Y(1S) as a function of $y^{Y}_{CM}$ in pPb collisions. The global uncertainty arises from the integrated luminosity uncertainty in pPb collisions.

Differential cross section times dimuon branching fraction of Y(2S) as a function of $y^{Y}_{CM}$ in pPb collisions. The global uncertainty arises from the integrated luminosity uncertainty in pPb collisions.

Differential cross section times dimuon branching fraction of Y(3S) as a function of $y^{Y}_{CM}$ in pPb collisions. The global uncertainty arises from the integrated luminosity uncertainty in pPb collisions.

Differential cross section times dimuon branching fraction of Y(1S) as a function of pT in pp collisions. The global uncertainty arises from the integrated luminosity uncertainty in pp collisions.

Differential cross section times dimuon branching fraction of Y(2S) as a function of pT in pp collisions. The global uncertainty arises from the integrated luminosity uncertainty in pp collisions.

Differential cross section times dimuon branching fraction of Y(3S) as a function of pT in pp collisions. The global uncertainty arises from the integrated luminosity uncertainty in pp collisions.

Differential cross section times dimuon branching fraction of Y(1S) as a function of $|y^{Y}_{CM}|$ in pp collisions. The global uncertainty arises from the integrated luminosity uncertainty in pp collisions.

Differential cross section times dimuon branching fraction of Y(2S) as a function of $|y^{Y}_{CM}|$ in pp collisions. The global uncertainty arises from the integrated luminosity uncertainty in pp collisions.

Differential cross section times dimuon branching fraction of Y(3S) as a function of $|y^{Y}_{CM}|$ in pp collisions. The global uncertainty arises from the integrated luminosity uncertainty in pp collisions.

Nuclear modification factor of Y(1S) as a function of pT. The global uncertainty arises from the integrated luminosity uncertainties in pPb and pp collisions.

Nuclear modification factor of Y(2S) as a function of pT. The global uncertainty arises from the integrated luminosity uncertainties in pPb and pp collisions.

Nuclear modification factor of Y(3S) as a function of pT. The global uncertainty arises from the integrated luminosity uncertainties in pPb and pp collisions.

Nuclear modification factor of Y(1S) as a function of $y^{Y}_{CM}$. The global uncertainty arises from the integrated luminosity uncertainties in pPb and pp collisions.

Nuclear modification factor of Y(2S) as a function of $y^{Y}_{CM}$. The global uncertainty arises from the integrated luminosity uncertainties in pPb and pp collisions.

Nuclear modification factor of Y(3S) as a function of $y^{Y}_{CM}$. The global uncertainty arises from the integrated luminosity uncertainties in pPb and pp collisions.

Nuclear modification factor of Y(1S) at forward and backward $y^{Y}_{CM}$ for pT < 6 GeV/c. The global uncertainty arises from the integrated luminosity uncertainties in pPb and pp collisions.

Nuclear modification factor of Y(2S) at forward and backward $y^{Y}_{CM}$ for pT < 6 GeV/c. The global uncertainty arises from the integrated luminosity uncertainties in pPb and pp collisions.

Nuclear modification factor of Y(3S) at forward and backward $y^{Y}_{CM}$ for pT < 6 GeV/c. The global uncertainty arises from the integrated luminosity uncertainties in pPb and pp collisions.

Nuclear modification factor of Y(1S) at forward and backward $y^{Y}_{CM}$ for 6 < pT < 30 GeV/c. The global uncertainty arises from the integrated luminosity uncertainties in pPb and pp collisions.

Nuclear modification factor of Y(2S) at forward and backward $y^{Y}_{CM}$ for 6 < pT < 30 GeV/c. The global uncertainty arises from the integrated luminosity uncertainties in pPb and pp collisions.

Nuclear modification factor of Y(3S) at forward and backward $y^{Y}_{CM}$ for 6 < pT < 30 GeV/c. The global uncertainty arises from the integrated luminosity uncertainties in pPb and pp collisions.

RFB of Y(1S) versus $N^{|\eta_{lab}|<2.4}_{tracks}$.

RFB of Y(2S) versus $N^{|\eta_{lab}|<2.4}_{tracks}$.

RFB of Y(3S) versus $N^{|\eta_{lab}|<2.4}_{tracks}$.

RFB of Y(1S) versus $E^{|\eta_{lab}|>4}_{T}$.

RFB of Y(2S) versus $E^{|\eta_{lab}|>4}_{T}$.

RFB of Y(3S) versus $E^{|\eta_{lab}|>4}_{T}$.

Nuclear modification factor of Y(1S), Y(2S), and Y(3S) integrated over pT and $y^{Y}_{CM}$. The global uncertainty arises from the integrated luminosity uncertainties in pPb and pp collisions.

Measured diferential cross sections as a function of the transverse momentum of the lepton from the W decay.

Measured diferential cross sections ratio $R=\sigma(W^+ + \overline{c}) / \sigma(W^- + c)$ as a function of the absolute value of the pseudorapidity of the lepton from the W decay.

Measured diferential cross sections ratio $R=\sigma(W^+ + \overline{c}) / \sigma(W^- + c)$ as a function of the transverse momentum of the lepton from the W decay.

Upper limits on the production cross section times branching fraction of the b* RH hypothesis at a 95% CL. Dashed colored lines show the expected limits from the l+jets and all-hadronic channels, where the latter start at resonance masses of 1.4 TeV. The observed and expected limits from the combination are shown as solid and dashed black lines, respectively. The green and yellow bands show the 68 and 95% confidence intervals on the combined expected limits.

Upper limits on the production cross section times branching fraction of the b* VL hypothesis at a 95% CL. Dashed colored lines show the expected limits from the l+jets and all-hadronic channels, where the latter start at resonance masses of 1.4 TeV. The observed and expected limits from the combination are shown as solid and dashed black lines, respectively. The green and yellow bands show the 68 and 95% confidence intervals on the combined expected limits.

Upper limits on the production cross section times branching fraction of the B+b hypothesis at a 95% CL. Dashed colored lines show the expected limits from the l+jets and all-hadronic channels, where the latter start at resonance masses of 1.4 TeV. The observed and expected limits from the combination are shown as solid and dashed black lines, respectively. The green and yellow bands show the 68 and 95% confidence intervals on the combined expected limits.

Upper limits on the production cross section times branching fraction of the B+t hypothesis at a 95% CL. Dashed colored lines show the expected limits from the l+jets and all-hadronic channels, where the latter start at resonance masses of 1.4 TeV. The observed and expected limits from the combination are shown as solid and dashed black lines, respectively. The green and yellow bands show the 68 and 95% confidence intervals on the combined expected limits.

Exclusion limit for BrHZX_BrXee

Exclusion limit for BrHZX_BrXmumu

Exclusion limit for BrHZX_BrXll

Exclusion limit for cah

Exclusion limit for cZh

Exclusion limit for kappa

The acceptance- and efficiency-corrected yields for the $\mathrm{B}^{+}$ mesons, scaled by $T_{\mathrm{AA}}$ and $N_{\text{MB}}$ in PbPb collisions at $\sqrt{s_{NN}}=5.02$ TeV. The results are shown as a function of the event $\langle N_{part} \rangle$.

The acceptance- and efficiency-corrected $\mathrm{B}^{0}_{\mathrm{s}}/\mathrm{B}^{+}$ yields in PbPb collisions at $\sqrt{s_{NN}}=5.02$. TeV. The results are shown as a function of the meson $p_T$.

The acceptance- and efficiency-corrected $\mathrm{B}^{0}_{\mathrm{s}}/\mathrm{B}^{+}$ yields in PbPb collisions at $\sqrt{s_{NN}}=5.02$. The results are shown as a function of the event $\langle N_{part} \rangle$.

The nuclear modification factor R$_{\rm AA}$, as a function of $z$ in the 0-20 and 20-30 collisions centrality ranges.

Dijet signal efficiencies as a function of the signal mass and lifetime for events satisfying all event and vertex requirements, with corrections based on systematic differences in the vertex reconstruction efficiency between data and simulation.

The distribution of $d_{\mathrm{BV}}$ for $\geq$5-track one-vertex events in data and three simulated multijet signal samples each with a mass of 1600 GeV. The production cross section for each signal model is assumed to be the lower limit excluded by CMS-EXO-17-018, corresponding to values of 0.8, 0.25, and 0.15 fb for the samples with $c\tau =$ 0.3, 1.0, and 10 mm, respectively. The last bin includes the overflow events. This bin includes one event in data with a vertex with large $d_{\mathrm{BV}}$ that appears to arise from tracks originating from separate pp interaction vertices, consistent with background.

Distribution of the $x$-$y$ distances between vertices, $d_{\mathrm{VV}}$, for 2017 and 2018 data. The background distribution $d_{\mathrm{VV}}^{\kern 0.15em\mathrm{C}}$ (blue continuous line) is constructed from one-vertex events in data, and is normalized to the number of two-vertex events in data with two 3-track vertices. The two vertical red dashed lines separate the regions used in the fit.

Distribution of the $x$-$y$ distances between vertices, $d_{\mathrm{VV}}$, for 2017 and 2018 data. The background distribution $d_{\mathrm{VV}}^{\kern 0.15em\mathrm{C}}$ (blue continuous line) is constructed from one-vertex events in data, and is normalized to the number of two-vertex events in data which have exactly one 4-track vertex and one 3-track vertex. The two vertical red dashed lines separate the regions used in the fit.

Distribution of the $x$-$y$ distances between vertices, $d_{\mathrm{VV}}$, for 2017 and 2018 data. The background distribution $d_{\mathrm{VV}}^{\kern 0.15em\mathrm{C}}$ (blue continuous line) is constructed from one-vertex events in data, and is normalized to the number of two-vertex events in data with two 4-track vertices. The two vertical red dashed lines separate the regions used in the fit.

Distribution of the $x$-$y$ distances between vertices, $d_{\mathrm{VV}}$, for 2017 and 2018 data. The background distribution $d_{\mathrm{VV}}^{\kern 0.15em\mathrm{C}}$ (blue continuous line) is constructed from one-vertex events in data, and is normalized using $\geq$5-track one-vertex event information. The two vertical red dashed lines separate the regions used in the fit.

Predicted yields for the background-only normalized template, predicted yields for three simulated multijet signals each with a mass of 1600 GeV, and the observed yield in each $d_{\mathrm{VV}}$ bin. The production cross section for each signal model is assumed to be the lower limit excluded by CMS-EXO-17-018, corresponding to values of 0.8, 0.25, and 0.15 fb for samples with $c\tau =$ 0.3, 1.0, and 10 mm, respectively. The uncertainties in the signal yields and the systematic uncertainties in the background prediction reflect the systematic uncertainties given in the text.

Observed 95% CL upper limits on the product of cross section and branching fraction squared for the multijet signals, as a function of mass and $c\tau$. The overlaid mass-lifetime exclusion curves assume pair-production cross sections for the neutralino (red) and gluino (purple) with 100% branching fraction to each model's respective decay mode specified. The solid black (dashed colored) lines represent the observed (median expected) limits at 95% CL. The thin black lines represent the variation of the observed limit within theoretical uncertainties of the signal cross section. The thin dashed colored lines represent the region containing 68% of the expected limit distribution under the background-only hypothesis. The observed limits from the CMS displaced jets search (CMS-EXO-19-021) are also shown in teal for comparison.

Observed 95% CL upper limits on the product of cross section and branching fraction squared for the multijet signals, as a function of mass and $c\tau$. The overlaid mass-lifetime exclusion curves assume pair-production cross sections for the neutralino (red) and gluino (purple) with 100% branching fraction to each model's respective decay mode specified. The solid black (dashed colored) lines represent the observed (median expected) limits at 95% CL. The thin black lines represent the variation of the observed limit within theoretical uncertainties of the signal cross section. The thin dashed colored lines represent the region containing 68% of the expected limit distribution under the background-only hypothesis. The observed limits from the CMS displaced jets search (CMS-EXO-19-021) are also shown in teal for comparison.

Observed 95% CL upper limits on the product of cross section and branching fraction squared for the multijet signals, as a function of mass and $c\tau$. The overlaid mass-lifetime exclusion curves assume pair-production cross sections for the neutralino (red) and gluino (purple) with 100% branching fraction to each model's respective decay mode specified. The solid black (dashed colored) lines represent the observed (median expected) limits at 95% CL. The thin black lines represent the variation of the observed limit within theoretical uncertainties of the signal cross section. The thin dashed colored lines represent the region containing 68% of the expected limit distribution under the background-only hypothesis. The observed limits from the CMS displaced jets search (CMS-EXO-19-021) are also shown in teal for comparison.

Observed 95% CL upper limits on the product of cross section and branching fraction squared for the dijet signals, as a function of mass and $c\tau$. The overlaid mass-lifetime exclusion curves assume pair-production cross sections for the top squark with 100% branching fraction to each model's respective decay mode specified. The solid black (dashed colored) lines represent the observed (median expected) limits at 95% CL. The thin black lines represent the variation of the observed limit within theoretical uncertainties of the signal cross section. The thin dashed colored lines represent the region containing 68% of the expected limit distribution under the background-only hypothesis. The observed limits from the CMS displaced jets search (CMS-EXO-19-021) are also shown in teal for comparison.

Observed 95% CL upper limits on the product of cross section and branching fraction squared for the dijet signals, as a function of mass and $c\tau$. The overlaid mass-lifetime exclusion curves assume pair-production cross sections for the top squark with 100% branching fraction to each model's respective decay mode specified. The solid black (dashed colored) lines represent the observed (median expected) limits at 95% CL. The thin black lines represent the variation of the observed limit within theoretical uncertainties of the signal cross section. The thin dashed colored lines represent the region containing 68% of the expected limit distribution under the background-only hypothesis. The observed limits from the CMS displaced jets search (CMS-EXO-19-021) are also shown in teal for comparison.

Observed and expected 95% CL upper limits on the product of cross section and branching fraction squared, as a function of mass for multijet signals, for a fixed $c\tau$ of 300um in the full Run-2 data set. The neutralino and gluino pair production cross sections are shown for the multijet signals.

Observed and expected 95% CL upper limits on the product of cross section and branching fraction squared, as a function of mass for dijet signals, for a fixed $c\tau$ of 300um in the full Run-2 data set. The top squark pair-production cross section is shown for the dijet signals.

Observed and expected 95% CL upper limits on the product of cross section and branching fraction squared, as a function of mass for multijet signals, for a fixed $c\tau$ of 1 mm in the full Run-2 data set. The neutralino and gluino pair production cross sections are shown for the multijet signals.

Observed and expected 95% CL upper limits on the product of cross section and branching fraction squared, as a function of mass for dijet signals, for a fixed $c\tau$ of 1 mm in the full Run-2 data set. The top squark pair-production cross section is shown for the dijet signals.

Observed and expected 95% CL upper limits on the product of cross section and branching fraction squared, as a function of mass for multijet signals, for a fixed $c\tau$ of 10 mm in the full Run-2 data set. The neutralino and gluino pair production cross sections are shown for the multijet signals.

Observed and expected 95% CL upper limits on the product of cross section and branching fraction squared, as a function of mass for dijet signals, for a fixed $c\tau$ of 10 mm in the full Run-2 data set. The top squark pair-production cross section is shown for the dijet signals.

Observed and expected 95% CL upper limits on the product of cross section and branching fraction squared, as a function of $c\tau$ for multijet signals, for a fixed mass of 800 GeV in the full Run-2 data set. The neutralino and gluino pair production cross sections are shown for the multijet signals.

Observed and expected 95% CL upper limits on the product of cross section and branching fraction squared, as a function of $c\tau$ for dijet signals, for a fixed mass of 800 GeV in the full Run-2 data set. The top squark pair-production cross section is shown for the dijet signals.

Observed and expected 95% CL upper limits on the product of cross section and branching fraction squared, as a function of $c\tau$ for multijet signals, for a fixed mass of 1600 GeV in the full Run-2 data set. The neutralino and gluino pair production cross sections are shown for the multijet signals.

Observed and expected 95% CL upper limits on the product of cross section and branching fraction squared, as a function of $c\tau$ for dijet signals, for a fixed mass of 1600 GeV in the full Run-2 data set. The top squark pair-production cross section is shown for the dijet signals.

Observed and expected 95% CL upper limits on the product of cross section and branching fraction squared, as a function of $c\tau$ for multijet signals, for a fixed mass of 2400 GeV in the full Run-2 data set. The neutralino and gluino pair production cross sections are shown for the multijet signals. For $m$ = 2400 GeV, the expected neutralino cross section is $\approx 8\times 10^{-5}$ fb and is not shown.

Observed and expected 95% CL upper limits on the product of cross section and branching fraction squared, as a function of $c\tau$ for dijet signals, for a fixed mass of 2400 GeV in the full Run-2 data set. The top squark pair-production cross section is shown for the dijet signals.

Data-to-simulation efficiency correction factors, shown for multijet and dijet signal topologies in several ranges of $c\tau$. Note that these correction factors account for the two long-lived particles in the simulated events, and are therefore the total correction factors used to scale event yields rather than the correction factors one would apply to individual vertices.

Distribution of the azimuthal angle between vertices, $\Delta\phi_{\mathrm{VV}}$, for 2017 and 2018 data. The background distribution (blue continuous line) is constructed from 3-track one-vertex events in data, and is normalized to the number of 3-track two-vertex events in data.

Distribution of the azimuthal angle between vertices, $\Delta\phi_{\mathrm{VV}}$, for 2017 and 2018 data. The background distribution (blue continuous line) is constructed from 4-track and 3-track one-vertex events in data, and is normalized to the number of two-vertex events in data which have exactly one 4-track vertex and one 3-track vertex.

Distribution of the azimuthal angle between vertices, $\Delta\phi_{\mathrm{VV}}$, for 2017 and 2018 data. The background distribution (blue continuous line) is constructed from 4-track one-vertex events in data, and is normalized to the number of 4-track two-vertex events in data.

Distribution of the azimuthal angle between vertices, $\Delta\phi_{\mathrm{VV}}$, for 2017 and 2018 data. The background distribution (blue continuous line) is constructed from $\geq$5-track one-vertex events in data, and is normalized using one-vertex event information. No $\geq$5-track two-vertex data events pass the selection.

The Z boson differential cross section as a function of |yZ|.

The Z boson differential cross section as a function of |yZ|.

The Z boson differential cross section as a function of |yZ|.

The Z boson differential cross section as a function of pTZ.

The Z boson differential cross section as a function of pTZ.

The Z boson differential cross section as a function of pTZ.

The TAA-normalized yields of Z bosons as a function of centrality.

The TAA-normalized yields of Z bosons as a function of centrality.

The TAA-normalized yields of Z bosons as a function of centrality.

Distributions of $\Delta\phi_{\mathrm{trk,Z}}$ in 30-50% centrality PbPb collisions at 5.02 TeV.

Distributions of $\Delta\phi_{\mathrm{trk,Z}}$ in 0-30% centrality PbPb collisions at 5.02 TeV.

PbPb - pp difference of $\Delta\phi_{\mathrm{trk,Z}}$ distributions for 70-90% centrality PbPb collisions at 5.02 TeV.

PbPb - pp difference of $\Delta\phi_{\mathrm{trk,Z}}$ distributions for 50-70% centrality PbPb collisions at 5.02 TeV.

PbPb - pp difference of $\Delta\phi_{\mathrm{trk,Z}}$ distributions for 30-50% centrality PbPb collisions at 5.02 TeV.

PbPb - pp difference of $\Delta\phi_{\mathrm{trk,Z}}$ distributions for 0-30% centrality PbPb collisions at 5.02 TeV.

Distributions of $\xi^{\mathrm{trk,Z}}_{\mathrm{T}}$ in pp collisions at 5.02 TeV.

Distributions of $\xi^{\mathrm{trk,Z}}_{\mathrm{T}}$ in 70-90% centrality PbPb collisions at 5.02 TeV.

Distributions of $\xi^{\mathrm{trk,Z}}_{\mathrm{T}}$ in 50-70% centrality PbPb collisions at 5.02 TeV.

Distributions of $\xi^{\mathrm{trk,Z}}_{\mathrm{T}}$ in 30-50% centrality PbPb collisions at 5.02 TeV.

Distributions of $\xi^{\mathrm{trk,Z}}_{\mathrm{T}}$ in 0-30% centrality PbPb collisions at 5.02 TeV.

PbPb / pp ratio of $\xi^{\mathrm{trk,Z}}_{\mathrm{T}}$ distributions for 70-90% centrality PbPb collisions at 5.02 TeV.

PbPb / pp ratio of $\xi^{\mathrm{trk,Z}}_{\mathrm{T}}$ distributions for 50-70% centrality PbPb collisions at 5.02 TeV.

PbPb / pp ratio of $\xi^{\mathrm{trk,Z}}_{\mathrm{T}}$ distributions for 30-50% centrality PbPb collisions at 5.02 TeV.

PbPb / pp ratio of $\xi^{\mathrm{trk,Z}}_{\mathrm{T}}$ distributions for 0-30% centrality PbPb collisions at 5.02 TeV.

Distributions of p$^{\mathrm{trk}}_{\mathrm{T}}$ in pp collisions at 5.02 TeV.

Distributions of p$^{\mathrm{trk}}_{\mathrm{T}}$ in pp collisions at 5.02 TeV.

Distributions of p$^{\mathrm{trk}}_{\mathrm{T}}$ in 70-90% centrality PbPb collisions at 5.02 TeV.

Distributions of p$^{\mathrm{trk}}_{\mathrm{T}}$ in 50-70% centrality PbPb collisions at 5.02 TeV.

Distributions of p$^{\mathrm{trk}}_{\mathrm{T}}$ in 30-50% centrality PbPb collisions at 5.02 TeV.

Distributions of p$^{\mathrm{trk}}_{\mathrm{T}}$ in 0-30% centrality PbPb collisions at 5.02 TeV.

PbPb / pp ratio of p$^{\mathrm{trk}}_{\mathrm{T}}$ distributions for 70-90% centrality PbPb collisions at 5.02 TeV.

PbPb / pp ratio of p$^{\mathrm{trk}}_{\mathrm{T}}$ distributions for 50-70% centrality PbPb collisions at 5.02 TeV.

PbPb / pp ratio of p$^{\mathrm{trk}}_{\mathrm{T}}$ distributions for 30-50% centrality PbPb collisions at 5.02 TeV.

PbPb / pp ratio of p$^{\mathrm{trk}}_{\mathrm{T}}$ distributions for 0-30% centrality PbPb collisions at 5.02 TeV.

Differential fiducial cross section (without the acceptance correction) for the DY process measured in the muon channel, as a function of $p_{\textrm{T}}$ for $15<m_{\mu\mu}<60$ GeV. The quoted error is the quadratic sum of the statistical and systematic uncertainties. The global normalisation uncertainty of 3.5% is listed separately.

Differential fiducial cross section (without the acceptance correction) for the DY process measured in the muon channel, as a function of $p_{\textrm{T}}$ for $60<m_{\mu\mu}<120$ GeV. The quoted error is the quadratic sum of the statistical and systematic uncertainties. The global normalisation uncertainty of 3.5% is listed separately.

Differential fiducial cross section (without the acceptance correction) for the DY process measured in the muon channel, as a function of $\phi^*$ for $15<m_{\mu\mu}<60$ GeV. The quoted error is the quadratic sum of the statistical and systematic uncertainties. The global normalisation uncertainty of 3.5% is listed separately.

Differential fiducial cross section (without the acceptance correction) for the DY process measured in the muon channel, as a function of $\phi^*$ for $60<m_{\mu\mu}<120$ GeV. The quoted error is the quadratic sum of the statistical and systematic uncertainties. The global normalisation uncertainty of 3.5% is listed separately.

Integrated fiducial cross section for the DY process measured in the muon channel. The quoted error is the quadratic sum of the statistical and systematic uncertainties. The global normalisation uncertainty of 3.5% is listed separately.

Differential cross section for the DY process measured in the muon channel, as a function of dimuon invariant mass. The quoted error is the quadratic sum of the statistical and systematic uncertainties. The global normalisation uncertainty of 3.5% is listed separately.

Differential cross section for the DY process measured in the muon channel, as a function of rapidity in the centre-of-mass frame for $15<m_{\mu\mu}<60$ GeV. The quoted error is the quadratic sum of the statistical and systematic uncertainties. The global normalisation uncertainty of 3.5% is listed separately.

Differential cross section for the DY process measured in the muon channel, as a function of rapidity in the centre-of-mass frame for $60<m_{\mu\mu}<120$ GeV. The quoted error is the quadratic sum of the statistical and systematic uncertainties. The global normalisation uncertainty of 3.5% is listed separately.

Differential cross section for the DY process measured in the muon channel, as a function of $p_{\textrm{T}}$ for $15<m_{\mu\mu}<60$ GeV. The quoted error is the quadratic sum of the statistical and systematic uncertainties. The global normalisation uncertainty of 3.5% is listed separately.

Differential cross section for the DY process measured in the muon channel, as a function of $p_{\textrm{T}}$ for $60<m_{\mu\mu}<120$ GeV. The quoted error is the quadratic sum of the statistical and systematic uncertainties. The global normalisation uncertainty of 3.5% is listed separately.

Differential cross section for the DY process measured in the muon channel, as a function of $\phi^*$ for $15<m_{\mu\mu}<60$ GeV. The quoted error is the quadratic sum of the statistical and systematic uncertainties. The global normalisation uncertainty of 3.5% is listed separately.

Differential cross section for the DY process measured in the muon channel, as a function of $\phi^*$ for $60<m_{\mu\mu}<120$ GeV. The quoted error is the quadratic sum of the statistical and systematic uncertainties. The global normalisation uncertainty of 3.5% is listed separately.

Integrated cross section for the DY process measured in the muon channel. The quoted error is the quadratic sum of the statistical and systematic uncertainties. The global normalisation uncertainty of 3.5% is listed separately.

Forward-backward ratios for $15<m_{\mu\mu}<60$ GeV. Quoted uncertainties are the quadratic sum of the statistical and systematic uncertainties.

Forward-backward ratios for $60<m_{\mu\mu}<120$ GeV. Quoted uncertainties are the quadratic sum of the statistical and systematic uncertainties.

Correlation matrix for the systematic uncertainties, excluding integrated luminosity, as a function of dimuon invariant mass.

Correlation matrix for the systematic uncertainties, excluding integrated luminosity, as a function of rapidity in the centre-of-mass frame for $15<m_{\mu\mu}<60$ GeV.

Correlation matrix for the systematic uncertainties, excluding integrated luminosity, as a function of rapidity in the centre-of-mass frame for $60<m_{\mu\mu}<120$ GeV.

Correlation matrix for the systematic uncertainties, excluding integrated luminosity, as a function of $p_{\textrm{T}}$ for $15<m_{\mu\mu}<60$ GeV.

Correlation matrix for the systematic uncertainties, excluding integrated luminosity, as a function of $p_{\textrm{T}}$ for $60<m_{\mu\mu}<120$ GeV.

Correlation matrix for the systematic uncertainties, excluding integrated luminosity, as a function of $\phi^*$ for $15<m_{\mu\mu}<60$ GeV.

Correlation matrix for the systematic uncertainties, excluding integrated luminosity, as a function of $\phi^*$ for $60<m_{\mu\mu}<120$ GeV.

Correlation matrix for the systematic uncertainties, excluding integrated luminosity, as a function of rapidity in the centre-of-mass frame, putting together low and high masses. Each bin is labeled lm_i or hm_i, where lm stands for $15<m_{\mu\mu}<60$ GeV, hm stands for $60<m_{\mu\mu}<120$ GeV, and i is the corresponding bin number in rapidity in the centre-of-mass frame. The global normalisation uncertainty of 3.5% is not included. Data from Figure [3, 4, 4].

Correlation matrix for the systematic uncertainties, excluding integrated luminosity, as a function of $p_{\textrm{T}}$, putting together low and high masses. Each bin is labeled lm_i or hm_i, where lm stands for $15<m_{\mu\mu}<60$ GeV, hm stands for $60<m_{\mu\mu}<120$ GeV, and i is the corresponding bin number in $p_{\textrm{T}}$. The global normalisation uncertainty of 3.5% is not included. Data from Figure [3, 4, 4].

Correlation matrix for the systematic uncertainties, excluding integrated luminosity, as a function of $\phi^*$, putting together low and high masses. Each bin is labeled lm_i or hm_i, where lm stands for $15<m_{\mu\mu}<60$ GeV, hm stands for $60<m_{\mu\mu}<120$ GeV, and i is the corresponding bin number in $\phi^*$. The global normalisation uncertainty of 3.5% is not included. Data from Figure [3, 4, 4].

Spectra of jets with |eta jet| < 2.0 for R = 0.6, for pp collisions and different centrality classes of PbPb collisions.

Spectra of jets with |eta jet| < 2.0 for R = 0.8, for pp collisions and different centrality classes of PbPb collisions.

Spectra of jets with |eta jet| < 2.0 for R = 1.0, for pp collisions and different centrality classes of PbPb collisions.

The spectra ratio for jets from pp collisions with |eta jet| < 2.0 for R = 0.2–0.8 with respect to R = 1.0.

The RAA for jets with |eta jet| < 2.0 as a function of jet PT for R = 0.2 and various centrality classes.

The RAA for jets with |eta jet| < 2.0 as a function of jet PT for R = 0.3 and various centrality classes.

The RAA for jets with |eta jet| < 2.0 as a function of jet PT for R = 0.4 and various centrality classes.

The RAA for jets with |eta jet| < 2.0 as a function of jet PT for R = 0.6 and various centrality classes.

The RAA for jets with |eta jet| < 2.0 as a function of jet PT for R = 0.8 and various centrality classes.

The RAA for jets with |eta jet| < 2.0 as a function of jet PT for R = 1.0 and various centrality classes.

The RAA-ratio for jets with |eta jet| < 2.0 as a function of R for R = 0.3–1.0 with respect to R = 0.2, in various event centrality classes and jet PT = 200-250 GeV.

The RAA-ratio for jets with |eta jet| < 2.0 as a function of R for R = 0.3–1.0 with respect to R = 0.2, in various event centrality classes and jet PT = 250-300 GeV.

The RAA-ratio for jets with |eta jet| < 2.0 as a function of R for R = 0.3–1.0 with respect to R = 0.2, in various event centrality classes and jet PT = 300-400 GeV.

The RAA-ratio for jets with |eta jet| < 2.0 as a function of R for R = 0.3–1.0 with respect to R = 0.2, in various event centrality classes and jet PT = 400-500 GeV.

The RAA-ratio for jets with |eta jet| < 2.0 as a function of R for R = 0.3–1.0 with respect to R = 0.2, in various event centrality classes and jet PT = 500-1000 GeV.

Three-jet events $p_{\mathrm{T}3}/p_{\mathrm{T}2}$ for large-angle radiation ($\Delta R_{23}$ > 1.0)

Three-jet events $\Delta R_{23}$ for soft radiation ($p_{\mathrm{T}3}/p_{\mathrm{T}2}$ < 0.3)

Three-jet events $\Delta R_{23}$ for soft radiation ($p_{\mathrm{T}3}/p_{\mathrm{T}2}$ < 0.3)

Three-jet events $\Delta R_{23}$ for hard radiation ($p_{\mathrm{T}3}/p_{\mathrm{T}2}$ > 0.6)

Three-jet events $\Delta R_{23}$ for hard radiation ($p_{\mathrm{T}3}/p_{\mathrm{T}2}$ > 0.6)

Three-jet events $p_{\mathrm{T}3}/p_{\mathrm{T}2}$ for small-angle radiation ($\Delta R_{23}$ < 1.0)

Three-jet events $p_{\mathrm{T}3}/p_{\mathrm{T}2}$ for small-angle radiation ($\Delta R_{23}$ < 1.0)

Three-jet events $p_{\mathrm{T}3}/p_{\mathrm{T}2}$ for large-angle radiation ($\Delta R_{23}$ > 1.0)

Three-jet events $p_{\mathrm{T}3}/p_{\mathrm{T}2}$ for large-angle radiation ($\Delta R_{23}$ > 1.0)

Three-jet events $\Delta R_{23}$ for soft radiation ($p_{\mathrm{T}3}/p_{\mathrm{T}2}$ < 0.3)

Three-jet events $\Delta R_{23}$ for soft radiation ($p_{\mathrm{T}3}/p_{\mathrm{T}2}$ < 0.3)

Three-jet events $\Delta R_{23}$ for hard radiation ($p_{\mathrm{T}3}/p_{\mathrm{T}2}$ > 0.6)

Three-jet events $\Delta R_{23}$ for hard radiation ($p_{\mathrm{T}3}/p_{\mathrm{T}2}$ > 0.6)

Z + two-jet events $p_{\mathrm{T}3}/p_{\mathrm{T}2}$ for small-angle radiation ($\Delta R_{23}$ < 1.0)

Z + two-jet events $p_{\mathrm{T}3}/p_{\mathrm{T}2}$ for small-angle radiation ($\Delta R_{23}$ < 1.0)

Z + two-jet events $p_{\mathrm{T}3}/p_{\mathrm{T}2}$ for large-angle radiation ($\Delta R_{23}$ > 1.0)

Z + two-jet events $p_{\mathrm{T}3}/p_{\mathrm{T}2}$ for large-angle radiation ($\Delta R_{23}$ > 1.0)

Z + two-jet events $\Delta R_{23}$ for soft radiation ($p_{\mathrm{T}3}/p_{\mathrm{T}2}$ < 0.3)

Z + two-jet events $\Delta R_{23}$ for soft radiation ($p_{\mathrm{T}3}/p_{\mathrm{T}2}$ < 0.3)

Z + two-jet events $\Delta R_{23}$ for hard radiation ($p_{\mathrm{T}3}/p_{\mathrm{T}2}$ > 0.6)

Z + two-jet events $\Delta R_{23}$ for hard radiation ($p_{\mathrm{T}3}/p_{\mathrm{T}2}$ > 0.6)

Neutron multiplicity dependence of acoplanarity ($\alpha$) from process $\gamma\gamma$ to $\mu^+\mu^-$ in ultraperipheral PbPb at $\sqrt{s_{NN}}=5.02$ TeV.

Neutron multiplicity dependence of acoplanarity ($\alpha$) from process $\gamma\gamma$ to $\mu^+\mu^-$ in ultraperipheral PbPb at $\sqrt{s_{NN}}=5.02$ TeV.

Neutron multiplicity dependence of acoplanarity ($\alpha$) from process $\gamma\gamma$ to $\mu^+\mu^-$ in ultraperipheral PbPb at $\sqrt{s_{NN}}=5.02$ TeV.

Neutron multiplicity dependence of average core acoplanarity ($<\alpha^{core}>$) distributions from process $\gamma\gamma$ to $\mu^+\mu^-$ in ultraperipheral PbPb at $\sqrt{s_{NN}}=5.02$ TeV.

Neutron multiplicity dependence of average invariant mass ($<m_{\mu\mu}>$) from process $\gamma\gamma$ to $\mu^+\mu^-$ in ultraperipheral PbPb at $\sqrt{s_{NN}}=5.02$ TeV.

Acoplanarity ($\alpha$) distributions from process $\gamma\gamma$ to $\mu^+\mu^-$ for 0n1n class in ultraperipheral PbPb at $\sqrt{s_{NN}}=5.02$ TeV. Dimuon rapidity is in the hemisphere containing larger neutron multiplicity.

Acoplanarity ($\alpha$) distributions from process $\gamma\gamma$ to $\mu^+\mu^-$ for 0nXn class in ultraperipheral PbPb at $\sqrt{s_{NN}}=5.02$ TeV. Dimuon rapidity is in the hemisphere containing larger neutron multiplicity.

Acoplanarity ($\alpha$) distributions from process $\gamma\gamma$ to $\mu^+\mu^-$ for 1nXn class in ultraperipheral PbPb at $\sqrt{s_{NN}}=5.02$ TeV. Dimuon rapidity is in the hemisphere containing larger neutron multiplicity.

Acoplanarity ($\alpha$) distributions from process $\gamma\gamma$ to $\mu^+\mu^-$ for 0n1n class in ultraperipheral PbPb at $\sqrt{s_{NN}}=5.02$ TeV. Dimuon rapidity is in the hemisphere containing smaller neutron multiplicity.

Acoplanarity ($\alpha$) distributions from process $\gamma\gamma$ to $\mu^+\mu^-$ for 0nXn class in ultraperipheral PbPb at $\sqrt{s_{NN}}=5.02$ TeV. Dimuon rapidity is in the hemisphere containing smaller neutron multiplicity.

Acoplanarity ($\alpha$) distributions from process $\gamma\gamma$ to $\mu^+\mu^-$ for 1nXn class in ultraperipheral PbPb at $\sqrt{s_{NN}}=5.02$ TeV. Dimuon rapidity is in the hemisphere containing smaller neutron multiplicity.

Prompt $D^0$ meson $v_3$ as a function of $p_T$ in PbPb collisions at $\sqrt{s_{NN}}=5.02~TeV$.

Prompt $D^0$ meson $v_3$ as a function of $p_T$ in PbPb collisions at $\sqrt{s_{NN}}=5.02~TeV$.

Prompt $D^0$ meson $v_3$ as a function of $p_T$ in PbPb collisions at $\sqrt{s_{NN}}=5.02~TeV$.

Prompt $D^0$ meson $v_2$ as a function of $p_T$ in PbPb collisions at $\sqrt{s_{NN}}=5.02~TeV$.

Prompt $D^0$ meson $v_2$ as a function of $p_T$ in PbPb collisions at $\sqrt{s_{NN}}=5.02~TeV$.

Prompt $D^0$ meson $v_2$ as a function of $p_T$ in PbPb collisions at $\sqrt{s_{NN}}=5.02~TeV$.

Prompt $D^0$ meson $v_3$ as a function of $p_T$ in PbPb collisions at $\sqrt{s_{NN}}=5.02~TeV$.

Prompt $D^0$ meson $v_3$ as a function of $p_T$ in PbPb collisions at $\sqrt{s_{NN}}=5.02~TeV$.

Prompt $D^0$ meson $v_3$ as a function of $p_T$ in PbPb collisions at $\sqrt{s_{NN}}=5.02~TeV$.

Prompt $D^0$ meson $v_2$ as a function of centrality in PbPb collisions at $\sqrt{s_{NN}}=5.02~TeV$.

Prompt $D^0$ meson $v_2$ as a function of centrality in PbPb collisions at $\sqrt{s_{NN}}=5.02~TeV$.

Prompt $D^0$ meson $v_3$ as a function of centrality in PbPb collisions at $\sqrt{s_{NN}}=5.02~TeV$.

Prompt $D^0$ meson $v_3$ as a function of centrality in PbPb collisions at $\sqrt{s_{NN}}=5.02~TeV$.

Prompt $D^0$ meson $v_2$ as a function of rapidity in PbPb collisions at $\sqrt{s_{NN}}=5.02~TeV$.

Prompt $D^0$ meson $v_3$ as a function of rapidity in PbPb collisions at $\sqrt{s_{NN}}=5.02~TeV$.

Prompt $D^0$ meson $\Delta v_2$ as a function of rapidity in PbPb collisions at $\sqrt{s_{NN}}=5.02~TeV$.

Results of elliptic flow, corrected for short range correlations, for prompt neutral D mesons, as a function of multiplicity for $|y_{lab}|< 1$, with 6$ < p_{T} < $8 GeV in pp collisions at 13 TeV.

Results of elliptic flow, corrected for short range correlations, for prompt neutral D mesons, as a function of multiplicity for $|y_{lab}|< 1$, with 2$ < p_{T} < $4 GeV in pPb collisions at 8.16 TeV.

Results of elliptic flow, corrected for short range correlations, for prompt neutral D mesons, as a function of multiplicity for $|y_{lab}|< 1$, with 4$ < p_{T} < $6 GeV in pPb collisions at 8.16 TeV.

Results of elliptic flow, corrected for short range correlations, for prompt neutral D mesons, as a function of multiplicity for $|y_{lab}|< 1$, with 6$ < p_{T} < $8 GeV in pPb collisions at 8.16 TeV.

Results of elliptic flow, corrected for short range correlations, for nonprompt neutral D mesons, as a function of transverse momenta for $|y_{lab}|< 1$, with $185 \leq N^{offline}_{trk} < 250$ in pPb collisions at 8.16 TeV.

Differential cross sections normalized to the fiducial cross section for the combined 4e, 2e2µ, and 4µ decay channels as a function of the invariant mass of the ZZ system

Differential cross sections normalized to the fiducial cross section for the combined 4e, 2e2µ, and 4µ decay channels as a function of azimuthal separation of the two Z bosons

Differential cross sections normalized to the fiducial cross section for the combined 4e, 2e2µ, and 4µ decay channels as a function of ∆R separation of the two Z bosons

Measured fiducial cross section for each data sample and combined. The first uncertainty is statistical, the second is experimental systematic, and the third is associated with the integrated luminosity.

Measured total σ(pp → ZZ) cross section for each data sample and combined. The first uncertainty is statistical, the second is experimental systematic, the third is theoretical systematic. The fourth uncertainty is associated with the integrated luminosity.

Expected and observed one-dimensional 95% CL limits on aTGC parameters. The corresponding constrains on EFT parameters are estimated using the transformation from Ref. [65].

Expected and observed one-dimensional 95% CL limits on aTGC parameters. The corresponding constrains on EFT parameters are estimated using the transformation from Ref. [65].

Measured fraction of events after unfolding for $N_J = 0, 1, \geq 2$ jets. The first uncertainty is statistical and the second combines systematic uncertainties from the response matrix and from the background subtraction.

Expected and observed 68% and 95% confidence intervals on the measurement of the Wilson coefficients associated with the three CP-preserving, dimension-6 operators.

Expected and observed 68% and 95% confidence intervals on the measurement of the Wilson coefficients associated with the three CP-preserving, dimension-6 operators.

Measured normalized differential cross sections with respect to the dilepton invariant mass.

Measured normalized differential cross sections with respect to the dilepton invariant mass.

Measured normalized differential cross sections with respect to the leading lepton $p_T$.

Measured normalized differential cross sections with respect to the leading lepton $p_T$.

Measured normalized differential cross sections with respect to the trailing lepton $p_T$.

Measured normalized differential cross sections with respect to the trailing lepton $p_T$.

Measured normalized differential cross sections with respect to the dilepton azimuthal angular separation.

Measured normalized differential cross sections with respect to the dilepton azimuthal angular separation.

Fiducial cross section for the production of $W^+W^−$ +0-jets as the $p_T$ threshold for jets is varied. The fiducial region is defined by two opposite-sign leptons with $p_T > 20$GeV and | η | < 2.5 excluding the products of τ lepton decay, and $m_{\ell\ell} > 20$GeV, $p_T^{\ell\ell} > 30$GeV, and $p_T^{\mathrm{miss}} > 30$GeV. Jets must have $p_T$ above the stated threshold, | η | < 4.5, and be separated from each of the two leptons by ∆R > 0.4. The total uncertainty is reported.

Fiducial cross section for the production of $W^+W^-$ +0-jets as the $p_T$ threshold for jets is varied. The fiducial region is defined by two opposite-sign leptons with $p_T > 20$GeV and |$\eta$| < 2.5 excluding the products of tau lepton decay, and $m_{\ell\ell} > 20$GeV, $p_T^{\ell\ell} > 30$GeV, and $p_T^{\mathrm{miss}} > 30$GeV. Jets must have $p_T$ above the stated threshold, |$\eta$| < 4.5, and be separated from each of the two leptons by dR > 0.4. The total uncertainty is reported.

Data from paper Table 4. Observed and expected exclusion limits for the aQGC parameters at 95% CL, without any form factors.

Data from paper Fig.4. Observed four lepton invariant mass distribution. The last bin includes overflow.

Measured cross section from the helicity fit, divided by bin width, for combination of muon and electron channel

Measured charge asymmetry from the helicity fit for combination of muon and electron channel

Measured cross section from the helicity fit, divided by bin width, for combination of muon and electron channel

Measured cross section from the helicity fit, divided by bin width, for combination of muon and electron channel

Measured charge asymmetry from the helicity fit for combination of muon and electron channel

Measured cross section from the helicity fit, divided by bin width, for combination of muon and electron channel

Measured cross section from the helicity fit, divided by bin width, for combination of muon and electron channel

Measured charge asymmetry from the helicity fit for combination of muon and electron channel

Measured cross section from the helicity fit, divided by bin width, for combination of muon and electron channel

Measured cross section from the helicity fit, divided by bin width, for combination of muon and electron channel

Impact of groups of uncertainties on normalized differential cross section versus $|y_{W}|$ for $W^{-}_{L}$

Impact of groups of uncertainties on charge asymmetry versus $|y_{W}|$ for $W_{L}$

Impact of groups of uncertainties on normalized differential cross section versus $|y_{W}|$ for $W^{+}_{L}$

Impact of groups of uncertainties on normalized differential cross section versus $|y_{W}|$ for $W^{-}_{R}$

Impact of groups of uncertainties on normalized differential cross section versus $|y_{W}|$ for $W^{+}_{R}$

Impact of groups of uncertainties on absolute differential cross section versus $|y_{W}|$ for $W^{+}_{R}$

Impact of groups of uncertainties on absolute differential cross section versus $|y_{W}|$ for $W^{+}_{L}$

Impact of groups of uncertainties on absolute differential cross section versus $|y_{W}|$ for $W^{-}_{L}$

Impact of groups of uncertainties on absolute differential cross section versus $|y_{W}|$ for $W^{-}_{R}$

Impact of groups of uncertainties on charge asymmetry versus $|y_{W}|$ for $W_{R}$

Impact of groups of uncertainties on absolute differential cross section versus $|y_{W}|$ for $W^{+}$

Impact of groups of uncertainties on absolute differential cross section versus $|y_{W}|$ for $W^{+}$

Impact of groups of uncertainties on unpolarized charge asymmetry versus $|y_{W}|$

Impact of groups of uncertainties on normalized differential cross section versus $|y_{W}|$ for $W^{+}$

Impact of groups of uncertainties on normalized differential cross section versus $|y_{W}|$ for $W^{+}$

Impact of groups of uncertainties on $A_{4}$ coefficient versus $|y_{W}|$ for $W^{+}$

Impact of groups of uncertainties on $A_{4}$ coefficient versus $|y_{W}|$ for $W^{+}$

Correlation matrix among normalized signal cross sections in the helicity fit, for combination of muon and electron channel. The cross sections are shown in Fig. 9 in paper

Correlation matrix among normalized signal cross sections in the helicity fit, for combination of muon and electron channel. The cross sections are shown in Fig. 9 in paper

Correlation matrix among PDF nuisances parameters in the helicity fit with fixed signal cross sections, for combination of muon and electron channel. The postfit values for these nuisance parameters are shown in Fig. 20 in paper

Postfit pulls and constraints for some nuisance parameters: $p_T^{W}$ binned $\mu_R$, $\mu_F$, $\mu_R\mu_F$ for $W_R$

Postfit pulls and constraints for some nuisance parameters: $p_T^{W}$ binned $\mu_R$, $\mu_F$, $\mu_R\mu_F$ for $W_L$

Postfit pulls and constraints for some nuisance parameters: PDFs and $\alpha_S$

Postfit pulls and constraints for all nuisance parameters in the W boson helicity fit with fixed signal cross sections, from combination of electron and muon channel. The convention adopted to name nuisance parameters in the tables is reported in glossary_nuisAndPois.txt

Postfit pulls and constraints for all nuisance parameters in the W boson helicity fit with floating signal cross sections, from combination of electron and muon channel. The convention adopted to name nuisance parameters in the tables is reported in glossary_nuisAndPois.txt

Measured double differential cross section from the double-differential cross section fit, divided by 2D-bin area, for combination of muon and electron channel

Measured double differential cross section from the double-differential cross section fit, divided by 2D-bin area, for combination of muon and electron channel

Measured double differential charge asymmetry from the double-differential cross section fit, for combination of muon and electron channel

Measured double differential cross section from the double-differential cross section fit, divided by 2D-bin area, for combination of muon and electron channel

Measured double differential cross section from the double-differential cross section fit, divided by 2D-bin area, for combination of muon and electron channel

Measured differential cross section from the double-differential cross section fit, divided by bin width, for combination of muon and electron channel

Measured differential cross section from the double-differential cross section fit, divided by bin width, for combination of muon and electron channel

Measured double differential cross section from the double-differential cross section fit, divided by 2D-bin area, for combination of muon and electron channel

Measured double differential cross section from the double-differential cross section fit, divided by 2D-bin area, for combination of muon and electron channel

Measured differential charge asymmetry from the double-differential cross section fit, for combination of muon and electron channel

Measured differential cross section from the double-differential cross section fit, divided by bin width, for combination of muon and electron channel

Measured differential cross section from the double-differential cross section fit, divided by bin width, for combination of muon and electron channel

Measured fiducial cross sections and ratio from the double-differential cross section fit, for combination of muon and electron channel

Measured differential cross section from the double-differential cross section fit, divided by bin width, for combination of muon and electron channel

Measured differential cross section from the double-differential cross section fit, divided by bin width, for combination of muon and electron channel

Measured differential charge asymmetry from the double-differential cross section fit, for combination of muon and electron channel

Measured differential cross section from the double-differential cross section fit, divided by bin width, for combination of muon and electron channel

Measured differential cross section from the double-differential cross section fit, divided by bin width, for combination of muon and electron channel

Impact of groups of uncertainties on charge asymmetry versus lepton $|\eta|$, for combination of muon and electron channel

Impact of groups of uncertainties on normalized differential cross section versus lepton $|\eta|$, for combination of muon and electron channel

Impact of groups of uncertainties on absolute differential cross section versus lepton $|\eta|$, for combination of muon and electron channel

Impact of groups of uncertainties on absolute differential cross section versus lepton $|\eta|$, for combination of muon and electron channel

Impact of groups of uncertainties on charge asymmetry versus lepton $p_{T}$, for combination of muon and electron channel

Impact of groups of uncertainties on normalized differential cross section versus lepton $p_{T}$, for combination of muon and electron channel

Impact of groups of uncertainties on normalized differential cross section versus lepton $p_{T}$, for combination of muon and electron channel

Impact of groups of uncertainties on absolute differential cross section versus lepton $p_{T}$, for combination of muon and electron channel

Impact of groups of uncertainties on absolute differential cross section versus lepton $p_{T}$, for combination of muon and electron channel

Impact of groups of uncertainties on normalized differential cross section versus lepton $|\eta|$, for combination of muon and electron channel

Postfit pulls and constraints for all nuisance parameters in the W boson double-differential cross section fit with floating signal cross sections, from combination of electron and muon channel. The convention adopted to name nuisance parameters in the tables is reported in glossary_nuisAndPois.txt

Cross section upper limit vs m(GLUINO) for SMS model T5ZZ.

Cross section upper limit vs m(GLUINO) for SMS model T5ZZ.

Cross section upper limit vs m(GLUINO) for SMS model T5ZZ.

Cross section vs m(GLUINO) for SMS model T5ZZ.

Cross section vs m(GLUINO) for SMS model T5ZZ.

Cross section vs m(GLUINO) for SMS model T5ZZ.

Number of events in the pTmiss CR, transfer factor, background prediction, and observed yield in each of the six pTmiss bins. The systematic uncertainties in the background prediction include the shape uncertainties in addition to the uncertainty in T. Also listed in the last column is the number of expected signal events and corresponding statistical uncertainties for one example mass point, m(GLUINO) = 1700 GeV. The last pTmiss bin includes overflows.

Pre-fit background covariance matrix $\sigma_{xy}$ for the 6 pTmiss bins.

Pre-fit background correlation matrix $\rho_{xy}$ for the 6 pTmiss bins.

Observed significance (in standard deviations) of the T5ZZ signal model as a function of the gluino mass.

Cut flow for the signal for two example mass points of the T5ZZ signal model. Here the hadronic baseline is defined by $N_{\mathrm{jets}}\ge 2$, $p_T^{\mathrm{miss}}$ > 300 GeV, $H_T$ > 300 GeV, $\Delta\phi$ cuts, and the isolated photon, lepton and track veto.

Mean $p_T$ values of the $\Upsilon(1$S$)$, $\Upsilon(2$S$)$, and $\Upsilon(3$S$)$ states with $p_T\,>\,0\,GeV$ and $|y|\,<\,1.2$ as a function of track multiplicity $N_{track}$

Ratio $\Upsilon(2$S$)\,/\,\Upsilon(1$S$)$ with $|y|\,<\,1.2$ as a function of track multiplicity $N_{track}$ in $0<p_T<5\,$GeV range

Ratio $\Upsilon(2$S$)\,/\,\Upsilon(1$S$)$ with $|y|\,<\,1.2$ as a function of track multiplicity $N_{track}$ in $5<p_T<7\,$GeV range

Ratio $\Upsilon(2$S$)\,/\,\Upsilon(1$S$)$ with $|y|\,<\,1.2$ as a function of track multiplicity $N_{track}$ in $7<p_T<9\,$GeV range

Ratio $\Upsilon(2$S$)\,/\,\Upsilon(1$S$)$ with $|y|\,<\,1.2$ as a function of track multiplicity $N_{track}$ in $9<p_T<11\,$GeV range

Ratio $\Upsilon(2$S$)\,/\,\Upsilon(1$S$)$ with $|y|\,<\,1.2$ as a function of track multiplicity $N_{track}$ in $11<p_T<15\,$GeV range

Ratio $\Upsilon(2$S$)\,/\,\Upsilon(1$S$)$ with $|y|\,<\,1.2$ as a function of track multiplicity $N_{track}$ in $15<p_T<20\,$GeV range

Ratio $\Upsilon(2$S$)\,/\,\Upsilon(1$S$)$ with $|y|\,<\,1.2$ as a function of track multiplicity $N_{track}$ in $20<p_T<50\,$GeV range

Ratio $\Upsilon(3$S$)\,/\,\Upsilon(1$S$)$ with $|y|\,<\,1.2$ as a function of track multiplicity $N_{track}$ in $0<p_T<5\,$GeV range

Ratio $\Upsilon(3$S$)\,/\,\Upsilon(1$S$)$ with $|y|\,<\,1.2$ as a function of track multiplicity $N_{track}$ in $5<p_T<7\,$GeV range

Ratio $\Upsilon(3$S$)\,/\,\Upsilon(1$S$)$ with $|y|\,<\,1.2$ as a function of track multiplicity $N_{track}$ in $7<p_T<9\,$GeV range

Ratio $\Upsilon(3$S$)\,/\,\Upsilon(1$S$)$ with $|y|\,<\,1.2$ as a function of track multiplicity $N_{track}$ in $9<p_T<11\,$GeV range

Ratio $\Upsilon(3$S$)\,/\,\Upsilon(1$S$)$ with $|y|\,<\,1.2$ as a function of track multiplicity $N_{track}$ in $11<p_T<15\,$GeV range

Ratio $\Upsilon(3$S$)\,/\,\Upsilon(1$S$)$ with $|y|\,<\,1.2$ as a function of track multiplicity $N_{track}$ in $15<p_T<20\,$GeV range

Ratio $\Upsilon(3$S$)\,/\,\Upsilon(1$S$)$ with $|y|\,<\,1.2$ as a function of track multiplicity $N_{track}$ in $20<p_T<50\,$GeV range

Ratios $\Upsilon(2$S$)\,/\,\Upsilon(1$S$)$ and $\Upsilon(3$S$)\,/\,\Upsilon(1$S$)$ as functions of "forward" track multiplicity $N_{track}^{\Delta\phi}$ for $\Upsilon(n$S$)$ states with $p_T\,>\,7\,GeV$ and $|y|\,<\,1.2$. Forward tracks are those with momentum direction in $\Delta\phi\,<\,\pi/3$ w.r.t. the $\Upsilon(n$S$)$ momentum direction.

Ratios $\Upsilon(2$S$)\,/\,\Upsilon(1$S$)$ and $\Upsilon(3$S$)\,/\,\Upsilon(1$S$)$ as functions of "transverse" track multiplicity $N_{track}^{\Delta\phi}$ for $\Upsilon(n$S$)$ states with $p_T\,>\,7\,GeV$ and $|y|\,<\,1.2$. Transverse tracks are those with momentum direction in $\pi/3\,<\,\Delta\phi\,<\,2\pi/3$ w.r.t. the $\Upsilon(n$S$)$ momentum direction.

Ratios $\Upsilon(2$S$)\,/\,\Upsilon(1$S$)$ and $\Upsilon(3$S$)\,/\,\Upsilon(1$S$)$ as functions of "backward" track multiplicity $N_{track}^{\Delta\phi}$ for $\Upsilon(n$S$)$ states with $p_T\,>\,7\,GeV$ and $|y|\,<\,1.2$. Backward tracks are those with momentum direction in $\Delta\phi\,>\,2\pi/3$ w.r.t. the $\Upsilon(n$S$)$ momentum direction.

Ratios $\Upsilon(2$S$)\,/\,\Upsilon(1$S$)$ and $\Upsilon(3$S$)\,/\,\Upsilon(1$S$)$ as functions of track multiplicity $N_{track}$ for $\Upsilon(n$S$)$ states with $p_T\,>\,7\,GeV$ and $|y|\,<\,1.2$ and $N^{\Delta R}_{track}\,=\,0$ charged particles produced in $\Delta R\,<\,0.5$ cone around $\Upsilon(n$S$)$ momentum direction.

Ratios $\Upsilon(2$S$)\,/\,\Upsilon(1$S$)$ and $\Upsilon(3$S$)\,/\,\Upsilon(1$S$)$ as functions of track multiplicity $N_{track}$ for $\Upsilon(n$S$)$ states with $p_T\,>\,7\,GeV$ and $|y|\,<\,1.2$ and $N^{\Delta R}_{track}\,=\,1$ charged particles produced in $\Delta R\,<\,0.5$ cone around $\Upsilon(n$S$)$ momentum direction.

Ratios $\Upsilon(2$S$)\,/\,\Upsilon(1$S$)$ and $\Upsilon(3$S$)\,/\,\Upsilon(1$S$)$ as functions of track multiplicity $N_{track}$ for $\Upsilon(n$S$)$ states with $p_T\,>\,7\,GeV$ and $|y|\,<\,1.2$ and $N^{\Delta R}_{track}\,=\,2$ charged particles produced in $\Delta R\,<\,0.5$ cone around $\Upsilon(n$S$)$ momentum direction.

Ratios $\Upsilon(2$S$)\,/\,\Upsilon(1$S$)$ and $\Upsilon(3$S$)\,/\,\Upsilon(1$S$)$ as functions of track multiplicity $N_{track}$ for $\Upsilon(n$S$)$ states with $p_T\,>\,7\,GeV$ and $|y|\,<\,1.2$ and $N^{\Delta R}_{track}\,>\,2$ charged particles produced in $\Delta R\,<\,0.5$ cone around $\Upsilon(n$S$)$ momentum direction.

Ratios $\Upsilon(2$S$)\,/\,\Upsilon(1$S$)$ and $\Upsilon(3$S$)\,/\,\Upsilon(1$S$)$ as functions of track multiplicity $N_{track}$ in transverse sphericity bin $0.00\,<\,S_T\,<\,0.55$ for $\Upsilon(n$S$)$ states with $p_T\,>\,7\,GeV$ and $|y|\,<\,1.2$.

Ratios $\Upsilon(2$S$)\,/\,\Upsilon(1$S$)$ and $\Upsilon(3$S$)\,/\,\Upsilon(1$S$)$ as functions of track multiplicity $N_{track}$ in transverse sphericity bin $0.55\,<\,S_T\,<\,0.70$ for $\Upsilon(n$S$)$ states with $p_T\,>\,7\,GeV$ and $|y|\,<\,1.2$.

Ratios $\Upsilon(2$S$)\,/\,\Upsilon(1$S$)$ and $\Upsilon(3$S$)\,/\,\Upsilon(1$S$)$ as functions of track multiplicity $N_{track}$ in transverse sphericity bin $0.70\,<\,S_T\,<\,0.85$ for $\Upsilon(n$S$)$ states with $p_T\,>\,7\,GeV$ and $|y|\,<\,1.2$.

Ratios $\Upsilon(2$S$)\,/\,\Upsilon(1$S$)$ and $\Upsilon(3$S$)\,/\,\Upsilon(1$S$)$ as functions of track multiplicity $N_{track}$ in transverse sphericity bin $0.85\,<\,S_T\,<\,1.00$ for $\Upsilon(n$S$)$ states with $p_T\,>\,7\,GeV$ and $|y|\,<\,1.2$.

Efficiency-corrected multiplicity bins used in the $\Upsilon(n$S$)$ ratio analysis and the corresponding mean number of charged particle tracks.

The correlation matrix for the njet measurement. The last bin is inclusive.

The fiducial integrated signal strength and cross section The uncertainty breakdown is given in terms of statistical (stat), experimental (exp), theoretical uncertainties on the background (bkg) and on the signal (sig), and the luminosity uncertainty (lumi). The fiducial cross section and its full uncertainty in each bin are also given.

Measured cross sections obtained with the BDT-based analyses. The uncertainties listed are statistical and systematic. For the results listed in the left (right) half of the table, Higgs boson contributions are counted as signal (background). The VVV cross section is calculated from the fit for \mu_{comb}. For ZZZ production, 95% confidence level upper limits are reported.

$v_{2}$ of $\Upsilon(\mathrm{1S})$ as a function of $p_{\mathrm{T}}$ in three centrality ranges, 10-30%, 30-50% and 50-90%.

$v_{2}$ of $\Upsilon(\mathrm{1S})$ as a function of $p_{\mathrm{T}}$ in 5-60% centrality range.

Charged particle yield distributions $Y(\Delta r)$ of b jets with $1 < p_{\text{T}}^{\text{trk}} < 12$ GeV are presented as functions of $\Delta r$.b jets with $p_T > 120$ GeV and charged particles with $1 < p^{\text{trk}}_{\text{T}} < 12$ GeV are used to construct the distributions as functions of $\Delta r$ differential $p_{\text{T}}^{\text{trk}}$ bins.

Charged particle yield differences of b to inclusive jets for $1 < p_{\text{T}}^{\text{trk}} < 12$ GeV are presented as functions of $\Delta r$.b jets with $p_T > 120$ GeV and charged particles with $1 < p^{\text{trk}}_{\text{T}} < 12$ GeV are used to construct the distributions as functions of $\Delta r$ differential $p_{\text{T}}^{\text{trk}}$ bins.

The jet shapes $\rho(\Delta r)$ of inclusive jets with $p_{\text{T}} > 120$ GeV and $p^{trk}_T > 1$ GeV are presented as functions of $\Delta r$ for differential $p_{\text{T}}^{\text{trk}}$ bin.

The jet shape distributions $\rho(\Delta r)$ of b jets with $p_{\text{T}} > 120$ GeV and $1< p^{\text{trk}}_{\text{T}} < 12$ GeV are presented as functions of $\Delta r$ for differential $p_{\text{T}}^{\text{trk}}$ bin.

The jet shapes $\rho (\Delta r)$ of inclusive jets with $p_{\text{T}} > 120$ GeV and $p^{\text{trk}}_{\text{T}} > 1$ GeV are presented as functions of $\Delta r.

The jet shapes $\rho (\Delta r)$ of b jets with $p_{\text{T}} > 120$ GeV and $p^{\text{trk}}_{\text{T}} > 1$ GeV are presented as functions of $\Delta r.

The b-to-inclusive jet shape ratios for $p_{\text{T}} > 120$ GeV and $p^{\text{trk}}_{\text{T}} > 1$ GeV are presented as functions of $\Delta r.

Ratio of differential cross section of AK1 jets with respect to AK4 jets a function of jet PT in the rapidity range 1.5<|y|<2.0. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of differential cross section of AK2 jets with respect to AK4 jets a function of jet PT in the rapidity range |y|<0.5. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of differential cross section of AK2 jets with respect to AK4 jets a function of jet PT in the rapidity range 0.5<|y|<1.0. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of differential cross section of AK2 jets with respect to AK4 jets a function of jet PT in the rapidity range 1.0<|y|<1.5. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of differential cross section of AK2 jets with respect to AK4 jets a function of jet PT in the rapidity range 1.5<|y|<2.0. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of differential cross section of AK3 jets with respect to AK4 jets a function of jet PT in the rapidity range |y|<0.5. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of differential cross section of AK3 jets with respect to AK4 jets a function of jet PT in the rapidity range 0.5<|y|<1.0. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of differential cross section of AK3 jets with respect to AK4 jets a function of jet PT in the rapidity range 1.0<|y|<1.5. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of differential cross section of AK3 jets with respect to AK4 jets a function of jet PT in the rapidity range 1.5<|y|<2.0. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of differential cross section of AK4 jets with respect to AK4 jets a function of jet PT in the rapidity range |y|<0.5. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of differential cross section of AK4 jets with respect to AK4 jets a function of jet PT in the rapidity range 0.5<|y|<1.0. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of differential cross section of AK4 jets with respect to AK4 jets a function of jet PT in the rapidity range 1.0<|y|<1.5. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of differential cross section of AK4 jets with respect to AK4 jets a function of jet PT in the rapidity range 1.5<|y|<2.0. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of differential cross section of AK5 jets with respect to AK4 jets a function of jet PT in the rapidity range |y|<0.5. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of differential cross section of AK5 jets with respect to AK4 jets a function of jet PT in the rapidity range 0.5<|y|<1.0. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of differential cross section of AK5 jets with respect to AK4 jets a function of jet PT in the rapidity range 1.0<|y|<1.5. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of differential cross section of AK5 jets with respect to AK4 jets a function of jet PT in the rapidity range 1.5<|y|<2.0. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of differential cross section of AK6 jets with respect to AK4 jets a function of jet PT in the rapidity range |y|<0.5. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of differential cross section of AK6 jets with respect to AK4 jets a function of jet PT in the rapidity range 0.5<|y|<1.0. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of differential cross section of AK6 jets with respect to AK4 jets a function of jet PT in the rapidity range 1.0<|y|<1.5. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of differential cross section of AK6 jets with respect to AK4 jets a function of jet PT in the rapidity range 1.5<|y|<2.0. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of differential cross section of AK7 jets with respect to AK4 jets a function of jet PT in the rapidity range |y|<0.5. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of differential cross section of AK7 jets with respect to AK4 jets a function of jet PT in the rapidity range 0.5<|y|<1.0. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of differential cross section of AK7 jets with respect to AK4 jets a function of jet PT in the rapidity range 1.0<|y|<1.5. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of differential cross section of AK7 jets with respect to AK4 jets a function of jet PT in the rapidity range 1.5<|y|<2.0. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of differential cross section of AK8 jets with respect to AK4 jets a function of jet PT in the rapidity range |y|<0.5. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of differential cross section of AK8 jets with respect to AK4 jets a function of jet PT in the rapidity range 0.5<|y|<1.0. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of differential cross section of AK8 jets with respect to AK4 jets a function of jet PT in the rapidity range 1.0<|y|<1.5. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of differential cross section of AK8 jets with respect to AK4 jets a function of jet PT in the rapidity range 1.5<|y|<2.0. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of differential cross section of AK9 jets with respect to AK4 jets a function of jet PT in the rapidity range |y|<0.5. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of differential cross section of AK9 jets with respect to AK4 jets a function of jet PT in the rapidity range 0.5<|y|<1.0. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of differential cross section of AK9 jets with respect to AK4 jets a function of jet PT in the rapidity range 1.0<|y|<1.5. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of differential cross section of AK9 jets with respect to AK4 jets a function of jet PT in the rapidity range 1.5<|y|<2.0. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of differential cross section of AK10 jets with respect to AK4 jets a function of jet PT in the rapidity range |y|<0.5. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of differential cross section of AK10 jets with respect to AK4 jets a function of jet PT in the rapidity range 0.5<|y|<1.0. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of differential cross section of AK10 jets with respect to AK4 jets a function of jet PT in the rapidity range 1.0<|y|<1.5. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of differential cross section of AK10 jets with respect to AK4 jets a function of jet PT in the rapidity range 1.5<|y|<2.0. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of differential cross section of AK11 jets with respect to AK4 jets a function of jet PT in the rapidity range |y|<0.5. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of differential cross section of AK11 jets with respect to AK4 jets a function of jet PT in the rapidity range 0.5<|y|<1.0. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of differential cross section of AK11 jets with respect to AK4 jets a function of jet PT in the rapidity range 1.0<|y|<1.5. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of differential cross section of AK11 jets with respect to AK4 jets a function of jet PT in the rapidity range 1.5<|y|<2.0. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of differential cross section of AK12 jets with respect to AK4 jets a function of jet PT in the rapidity range |y|<0.5. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of differential cross section of AK12 jets with respect to AK4 jets a function of jet PT in the rapidity range 0.5<|y|<1.0. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of differential cross section of AK12 jets with respect to AK4 jets a function of jet PT in the rapidity range 1.0<|y|<1.5. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of differential cross section of AK12 jets with respect to AK4 jets a function of jet PT in the rapidity range 1.5<|y|<2.0. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of cross section of inclusive anti-KT jets with respect to AK4 jets as a function of jet size in the rapidity range |y|<0.5 and PT 84 < p_{T} < 97 GeV. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of cross section of inclusive anti-KT jets with respect to AK4 jets as a function of jet size in the rapidity range |y|<0.5 and PT 97 < p_{T} < 133 GeV. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of cross section of inclusive anti-KT jets with respect to AK4 jets as a function of jet size in the rapidity range |y|<0.5 and PT 133 < p_{T} < 196 GeV. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of cross section of inclusive anti-KT jets with respect to AK4 jets as a function of jet size in the rapidity range |y|<0.5 and PT 196 < p_{T} < 272 GeV. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of cross section of inclusive anti-KT jets with respect to AK4 jets as a function of jet size in the rapidity range |y|<0.5 and PT 272 < p_{T} < 330 GeV. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of cross section of inclusive anti-KT jets with respect to AK4 jets as a function of jet size in the rapidity range |y|<0.5 and PT 330 < p_{T} < 395 GeV. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of cross section of inclusive anti-KT jets with respect to AK4 jets as a function of jet size in the rapidity range |y|<0.5 and PT 395 < p_{T} < 468 GeV. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of cross section of inclusive anti-KT jets with respect to AK4 jets as a function of jet size in the rapidity range |y|<0.5 and PT 468 < p_{T} < 548 GeV. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of cross section of inclusive anti-KT jets with respect to AK4 jets as a function of jet size in the rapidity range |y|<0.5 and PT 548 < p_{T} < 638 GeV. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of cross section of inclusive anti-KT jets with respect to AK4 jets as a function of jet size in the rapidity range |y|<0.5 and PT 638 < p_{T} < 1588 GeV. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of cross section of inclusive anti-KT jets with respect to AK4 jets as a function of jet size in the rapidity range 0.5<|y|<1.0 and PT 84 < p_{T} < 97 GeV. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of cross section of inclusive anti-KT jets with respect to AK4 jets as a function of jet size in the rapidity range 0.5<|y|<1.0 and PT 97 < p_{T} < 133 GeV. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of cross section of inclusive anti-KT jets with respect to AK4 jets as a function of jet size in the rapidity range 0.5<|y|<1.0 and PT 133 < p_{T} < 196 GeV. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of cross section of inclusive anti-KT jets with respect to AK4 jets as a function of jet size in the rapidity range 0.5<|y|<1.0 and PT 196 < p_{T} < 272 GeV. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of cross section of inclusive anti-KT jets with respect to AK4 jets as a function of jet size in the rapidity range 0.5<|y|<1.0 and PT 272 < p_{T} < 330 GeV. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of cross section of inclusive anti-KT jets with respect to AK4 jets as a function of jet size in the rapidity range 0.5<|y|<1.0 and PT 330 < p_{T} < 395 GeV. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of cross section of inclusive anti-KT jets with respect to AK4 jets as a function of jet size in the rapidity range 0.5<|y|<1.0 and PT 395 < p_{T} < 468 GeV. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of cross section of inclusive anti-KT jets with respect to AK4 jets as a function of jet size in the rapidity range 0.5<|y|<1.0 and PT 468 < p_{T} < 548 GeV. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of cross section of inclusive anti-KT jets with respect to AK4 jets as a function of jet size in the rapidity range 0.5<|y|<1.0 and PT 548 < p_{T} < 638 GeV. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of cross section of inclusive anti-KT jets with respect to AK4 jets as a function of jet size in the rapidity range 0.5<|y|<1.0 and PT 638 < p_{T} < 1588 GeV. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of cross section of inclusive anti-KT jets with respect to AK4 jets as a function of jet size in the rapidity range 1.0<|y|<1.5 and PT 84 < p_{T} < 97 GeV. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of cross section of inclusive anti-KT jets with respect to AK4 jets as a function of jet size in the rapidity range 1.0<|y|<1.5 and PT 97 < p_{T} < 133 GeV. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of cross section of inclusive anti-KT jets with respect to AK4 jets as a function of jet size in the rapidity range 1.0<|y|<1.5 and PT 133 < p_{T} < 196 GeV. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of cross section of inclusive anti-KT jets with respect to AK4 jets as a function of jet size in the rapidity range 1.0<|y|<1.5 and PT 196 < p_{T} < 272 GeV. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of cross section of inclusive anti-KT jets with respect to AK4 jets as a function of jet size in the rapidity range 1.0<|y|<1.5 and PT 272 < p_{T} < 330 GeV. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of cross section of inclusive anti-KT jets with respect to AK4 jets as a function of jet size in the rapidity range 1.0<|y|<1.5 and PT 330 < p_{T} < 395 GeV. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of cross section of inclusive anti-KT jets with respect to AK4 jets as a function of jet size in the rapidity range 1.0<|y|<1.5 and PT 395 < p_{T} < 468 GeV. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of cross section of inclusive anti-KT jets with respect to AK4 jets as a function of jet size in the rapidity range 1.0<|y|<1.5 and PT 468 < p_{T} < 548 GeV. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of cross section of inclusive anti-KT jets with respect to AK4 jets as a function of jet size in the rapidity range 1.0<|y|<1.5 and PT 548 < p_{T} < 638 GeV. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of cross section of inclusive anti-KT jets with respect to AK4 jets as a function of jet size in the rapidity range 1.0<|y|<1.5 and PT 638 < p_{T} < 1588 GeV. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of cross section of inclusive anti-KT jets with respect to AK4 jets as a function of jet size in the rapidity range 1.5<|y|<2.0 and PT 84 < p_{T} < 97 GeV. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of cross section of inclusive anti-KT jets with respect to AK4 jets as a function of jet size in the rapidity range 1.5<|y|<2.0 and PT 97 < p_{T} < 133 GeV. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of cross section of inclusive anti-KT jets with respect to AK4 jets as a function of jet size in the rapidity range 1.5<|y|<2.0 and PT 133 < p_{T} < 196 GeV. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of cross section of inclusive anti-KT jets with respect to AK4 jets as a function of jet size in the rapidity range 1.5<|y|<2.0 and PT 196 < p_{T} < 272 GeV. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of cross section of inclusive anti-KT jets with respect to AK4 jets as a function of jet size in the rapidity range 1.5<|y|<2.0 and PT 272 < p_{T} < 330 GeV. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of cross section of inclusive anti-KT jets with respect to AK4 jets as a function of jet size in the rapidity range 1.5<|y|<2.0 and PT 330 < p_{T} < 395 GeV. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of cross section of inclusive anti-KT jets with respect to AK4 jets as a function of jet size in the rapidity range 1.5<|y|<2.0 and PT 395 < p_{T} < 468 GeV. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of cross section of inclusive anti-KT jets with respect to AK4 jets as a function of jet size in the rapidity range 1.5<|y|<2.0 and PT 468 < p_{T} < 548 GeV. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of cross section of inclusive anti-KT jets with respect to AK4 jets as a function of jet size in the rapidity range 1.5<|y|<2.0 and PT 548 < p_{T} < 638 GeV. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Ratio of cross section of inclusive anti-KT jets with respect to AK4 jets as a function of jet size in the rapidity range 1.5<|y|<2.0 and PT 638 < p_{T} < 1588 GeV. The nonperturbative correction can be used to scale fixed-order theory prediction to compare to data at particle level.

Expected and observed yields from the standard model processeses in the WW signal region. The combination of the statistical and systematic uncertainties are shown. The predicted yields are shown with their best-fit normalizations from the simultaneous fit.

Expected and observed yields from the standard model processeses in the WW signal region. The combination of the statistical and systematic uncertainties are shown. The predicted yields are shown with their best-fit normalizations from the simultaneous fit.

Expected and observed yields from the standard model processeses in the WW signal region. The combination of the statistical and systematic uncertainties are shown. The predicted yields are shown with their best-fit normalizations from the simultaneous fit.

Expected and observed yields from the standard model processeses in the WZ signal region. The combination of the statistical and systematic uncertainties are shown. The predicted yields are shown with their best-fit normalizations from the simultaneous fit.

Expected and observed yields from the standard model processeses in the WZ signal region. The combination of the statistical and systematic uncertainties are shown. The predicted yields are shown with their best-fit normalizations from the simultaneous fit.

Expected and observed yields from the standard model processeses in the WZ signal region. The combination of the statistical and systematic uncertainties are shown. The predicted yields are shown with their best-fit normalizations from the simultaneous fit.

The measured inclusive fiducial cross section measurements. The WW fiducial region is defined by requiring two same-sign leptons with $p_{T}>20$, $|\eta|<2.5$, and $m_{ll}>20$, and two jets with $m_{jj}>500$ and $|\Delta \eta_{jj}|>2.5$. The jets at generator level are clustered from stable particles, excluding neutrinos, using the anti-kt clustering algorithm with R = 0.4, and are required to have $p_{T}>50$ and $|\eta|<4.7$. The jets within $\Delta R<0.4$ of the selected charged leptons are not included. The WZ fiducial region is defined by requiring three leptons with $p_{T}>20$, $|\eta|<2.5$, a pair of opposite charge same-flavor lepton pair with $|m_{ll}-m_{Z}|<15$, and two jets with $m_{jj}>500$ and $|\Delta \eta_{jj}|>2.5$.

The measured inclusive fiducial cross section measurements. The WW fiducial region is defined by requiring two same-sign leptons with $p_{T}>20$, $|\eta|<2.5$, and $m_{ll}>20$, and two jets with $m_{jj}>500$ and $|\Delta \eta_{jj}|>2.5$. The jets at generator level are clustered from stable particles, excluding neutrinos, using the anti-kt clustering algorithm with R = 0.4, and are required to have $p_{T}>50$ and $|\eta|<4.7$. The jets within $\Delta R<0.4$ of the selected charged leptons are not included. The WZ fiducial region is defined by requiring three leptons with $p_{T}>20$, $|\eta|<2.5$, a pair of opposite charge same-flavor lepton pair with $|m_{ll}-m_{Z}|<15$, and two jets with $m_{jj}>500$ and $|\Delta \eta_{jj}|>2.5$.

The measured inclusive fiducial cross section measurements. The WW fiducial region is defined by requiring two same-sign leptons with $p_{T}>20$, $|\eta|<2.5$, and $m_{ll}>20$, and two jets with $m_{jj}>500$ and $|\Delta \eta_{jj}|>2.5$. The jets at generator level are clustered from stable particles, excluding neutrinos, using the anti-kt clustering algorithm with R = 0.4, and are required to have $p_{T}>50$ and $|\eta|<4.7$. The jets within $\Delta R<0.4$ of the selected charged leptons are not included. The WZ fiducial region is defined by requiring three leptons with $p_{T}>20$, $|\eta|<2.5$, a pair of opposite charge same-flavor lepton pair with $|m_{ll}-m_{Z}|<15$, and two jets with $m_{jj}>500$ and $|\Delta \eta_{jj}|>2.5$.

Distributions of $m_{jj}$ in the WW signal region.

Distributions of $m_{jj}$ in the WW signal region.

Distributions of $m_{jj}$ in the WW signal region.

Distributions of $m_{ll}$ in the WW signal region.

Distributions of $m_{ll}$ in the WW signal region.

Distributions of $m_{ll}$ in the WW signal region.

Distributions of $m_{jj}$ in the WZ signal region.

Distributions of $m_{jj}$ in the WZ signal region.

Distributions of $m_{jj}$ in the WZ signal region.

Distributions of BDT score in the WZ signal region.

Distributions of BDT score in the WZ signal region.

Distributions of BDT score in the WZ signal region.

Absolute WW cross section in $m_{jj}$ bins.

Absolute WW cross section in $m_{jj}$ bins.

Absolute WW cross section in $m_{jj}$ bins.

Normalized WW cross section in $m_{jj}$ bins.

Normalized WW cross section in $m_{jj}$ bins.

Normalized WW cross section in $m_{jj}$ bins.

Absolute WW cross section in $m_{ll}$ bins.

Absolute WW cross section in $m_{ll}$ bins.

Absolute WW cross section in $m_{ll}$ bins.

Normalized WW cross section in $m_{ll}$ bins.

Normalized WW cross section in $m_{ll}$ bins.

Normalized WW cross section in $m_{ll}$ bins.

Absolute WW cross section in $p_{T}^{l max}$ bins.

Absolute WW cross section in $p_{T}^{l max}$ bins.

Absolute WW cross section in $p_{T}^{l max}$ bins.

Normalized WW cross section in $p_{T}^{l max}$ bins.

Normalized WW cross section in $p_{T}^{l max}$ bins.

Normalized WW cross section in $p_{T}^{l max}$ bins.

Absolute WZ cross section in $m_{jj}$ bins.

Absolute WZ cross section in $m_{jj}$ bins.

Absolute WZ cross section in $m_{jj}$ bins.

Normalized WZ cross section in $m_{jj}$ bins.

Normalized WZ cross section in $m_{jj}$ bins.

Normalized WZ cross section in $m_{jj}$ bins.

Distributions of $m_{T}^{WW}$ in the WW signal region.

Distributions of $m_{T}^{WW}$ in the WW signal region.

Distributions of $m_{T}^{WW}$ in the WW signal region.

Distributions of $m_{T}^{WZ}$ in the WZ signal region.

Distributions of $m_{T}^{WZ}$ in the WZ signal region.

Distributions of $m_{T}^{WZ}$ in the WZ signal region.

Observed and expected lower and upper 95\% confidence level limits in TeV$^{-4}$ on the parameters of the quartic, obtained without using any unitarization procedure.

Observed and expected lower and upper 95\% confidence level limits in TeV$^{-4}$ on the parameters of the quartic, obtained without using any unitarization procedure.

Observed and expected lower and upper 95\% confidence level limits in TeV$^{-4}$ on the parameters of the quartic, obtained without using any unitarization procedure.

Observed and expected lower and upper 95\% confidence level limits in TeV$^{-4}$ on the parameters of the quartic by cutting the EFT expansion at the unitarity limit.

Observed and expected lower and upper 95\% confidence level limits in TeV$^{-4}$ on the parameters of the quartic by cutting the EFT expansion at the unitarity limit.

Observed and expected lower and upper 95\% confidence level limits in TeV$^{-4}$ on the parameters of the quartic by cutting the EFT expansion at the unitarity limit.

The $m_{W}^{T}$ distribution from data (points) and simulation (shaded histograms) in the 2j1t (left) and 3j1t (right) categories for the muon (upper) and electron (lower) channels. The vertical lines on the points and the hatched bands show the experimental and MC statistical uncertainties, respectively. The expected distribution from the STq,b+STb,q processes (multiplied by a factor of 1000) is shown by the solid blue line. The lower panels show the ratio of the data to the MC prediction.

Distributions of the two most discriminating variables from data (points) and simulation (shaded histograms) in the 2j1t category: the $|\eta|$ of the non-b-tagged jet $|\eta_{j^{'}}|$ (left) and the invariant mass of lepton and b jet momenta system (right), shown for the muon (upper) and electron (lower) channels, respectively. The vertical lines on the points and the hatched bands show the experimental and MC statistical uncertainties, respectively. The expected distributionfrom the STq,b+STb,q processes (multiplied by a factor of 1000) is shown by the solid blue line. The lower panels show the ratio of the data to the MC prediction.

Distributions of the two most discriminating variables from data (points) and simulation (shaded histograms) in the 2j1t category: the $|\eta|$ of the non-b-tagged jet $|\eta_{j^{'}}|$ (left) and the invariant mass of lepton and b jet momenta system (right), shown for the muon (upper) and electron (lower) channels, respectively. The vertical lines on the points and the hatched bands show the experimental and MC statistical uncertainties, respectively. The expected distributionfrom the STq,b+STb,q processes (multiplied by a factor of 1000) is shown by the solid blue line. The lower panels show the ratio of the data to the MC prediction.

Distributions of the two most discriminating variables from data (points) and simulation (shaded histograms) in the 2j1t category: the $|\eta|$ of the non-b-tagged jet $|\eta_{j^{'}}|$ (left) and the invariant mass of lepton and b jet momenta system (right), shown for the muon (upper) and electron (lower) channels, respectively. The vertical lines on the points and the hatched bands show the experimental and MC statistical uncertainties, respectively. The expected distributionfrom the STq,b+STb,q processes (multiplied by a factor of 1000) is shown by the solid blue line. The lower panels show the ratio of the data to the MC prediction.

Distributions of the two most discriminating variables from data (points) and simulation (shaded histograms) in the 2j1t category: the $|\eta|$ of the non-b-tagged jet $|\eta_{j^{'}}|$ (left) and the invariant mass of lepton and b jet momenta system (right), shown for the muon (upper) and electron (lower) channels, respectively. The vertical lines on the points and the hatched bands show the experimental and MC statistical uncertainties, respectively. The expected distributionfrom the STq,b+STb,q processes (multiplied by a factor of 1000) is shown by the solid blue line. The lower panels show the ratio of the data to the MC prediction.

Distributions of the two most discriminating variables from data (points) and simulation (shaded histograms) in the 3j1t category: the $p_{T}^{miss}$ in the transverse plane (left) and the value of the MVA b tagger discriminator when applied to the extra jet (right) are shown for the muon (upper) and electron (lower) channels, respectively. The vertical lines on the points andthe hatched bands show the experimental and MC statistical uncertainties, respectively. The expected distribution from the STq,b+STb,q processes (multiplied by a factor of 1000) is shown by the solid blue line. The lower panels show the ratio of the data to the MC prediction.

Distributions of the two most discriminating variables from data (points) and simulation (shaded histograms) in the 3j1t category: the $p_{T}^{miss}$ in the transverse plane (left) and the value of the MVA b tagger discriminator when applied to the extra jet (right) are shown for the muon (upper) and electron (lower) channels, respectively. The vertical lines on the points andthe hatched bands show the experimental and MC statistical uncertainties, respectively. The expected distribution from the STq,b+STb,q processes (multiplied by a factor of 1000) is shown by the solid blue line. The lower panels show the ratio of the data to the MC prediction.

Distributions of the two most discriminating variables from data (points) and simulation (shaded histograms) in the 3j1t category: the $p_{T}^{miss}$ in the transverse plane (left) and the value of the MVA b tagger discriminator when applied to the extra jet (right) are shown for the muon (upper) and electron (lower) channels, respectively. The vertical lines on the points andthe hatched bands show the experimental and MC statistical uncertainties, respectively. The expected distribution from the STq,b+STb,q processes (multiplied by a factor of 1000) is shown by the solid blue line. The lower panels show the ratio of the data to the MC prediction.

Distributions of the two most discriminating variables from data (points) and simulation (shaded histograms) in the 3j1t category: the $p_{T}^{miss}$ in the transverse plane (left) and the value of the MVA b tagger discriminator when applied to the extra jet (right) are shown for the muon (upper) and electron (lower) channels, respectively. The vertical lines on the points andthe hatched bands show the experimental and MC statistical uncertainties, respectively. The expected distribution from the STq,b+STb,q processes (multiplied by a factor of 1000) is shown by the solid blue line. The lower panels show the ratio of the data to the MC prediction.

Distributions of the two most discriminating variables from data (points) and simulation (shaded histograms) in the 3j2t category: the $|\eta|$ of the non-b-tagged jet $|\eta_{j^{'}}|$ (left) and the invariant mass of lepton and non-b-tagged jet system (right) are shown for the muon (upper) and electron (lower) channels, respectively. The vertical lines on the points and the hatched bands show the experimental and MC statistical uncertainties, respectively. The expected distribution from the STq,b+STb,q processes (multiplied by a factor of 1000) is shown by the solid blue line. The lower panels show the ratio of the data to the MC prediction.

Distributions of the two most discriminating variables from data (points) and simulation (shaded histograms) in the 3j2t category: the $|\eta|$ of the non-b-tagged jet $|\eta_{j^{'}}|$ (left) and the invariant mass of lepton and non-b-tagged jet system (right) are shown for the muon (upper) and electron (lower) channels, respectively. The vertical lines on the points and the hatched bands show the experimental and MC statistical uncertainties, respectively. The expected distribution from the STq,b+STb,q processes (multiplied by a factor of 1000) is shown by the solid blue line. The lower panels show the ratio of the data to the MC prediction.

Distributions of the two most discriminating variables from data (points) and simulation (shaded histograms) in the 3j2t category: the $|\eta|$ of the non-b-tagged jet $|\eta_{j^{'}}|$ (left) and the invariant mass of lepton and non-b-tagged jet system (right) are shown for the muon (upper) and electron (lower) channels, respectively. The vertical lines on the points and the hatched bands show the experimental and MC statistical uncertainties, respectively. The expected distribution from the STq,b+STb,q processes (multiplied by a factor of 1000) is shown by the solid blue line. The lower panels show the ratio of the data to the MC prediction.

Distributions of the two most discriminating variables from data (points) and simulation (shaded histograms) in the 3j2t category: the $|\eta|$ of the non-b-tagged jet $|\eta_{j^{'}}|$ (left) and the invariant mass of lepton and non-b-tagged jet system (right) are shown for the muon (upper) and electron (lower) channels, respectively. The vertical lines on the points and the hatched bands show the experimental and MC statistical uncertainties, respectively. The expected distribution from the STq,b+STb,q processes (multiplied by a factor of 1000) is shown by the solid blue line. The lower panels show the ratio of the data to the MC prediction.

Distribution of the multivariate discriminators, comparing data to simulation normalised after the fit procedure, for the muon channel on the left and for the electron channel on the right, for 2j1t (upper), 3j1t (middle), and 3j2t (lower). The vertical lines on the points and the hatched bands show the experimental and fit uncertainties, respectively. The expected distribution from the STq,b+STb,q processes (multiplied by a factor of 1000) is shown by the solid blue line. The lower panels show the ratio of the data to the fit.

Distribution of the multivariate discriminators, comparing data to simulation normalised after the fit procedure, for the muon channel on the left and for the electron channel on the right, for 2j1t (upper), 3j1t (middle), and 3j2t (lower). The vertical lines on the points and the hatched bands show the experimental and fit uncertainties, respectively. The expected distribution from the STq,b+STb,q processes (multiplied by a factor of 1000) is shown by the solid blue line. The lower panels show the ratio of the data to the fit.

Distribution of the multivariate discriminators, comparing data to simulation normalised after the fit procedure, for the muon channel on the left and for the electron channel on the right, for 2j1t (upper), 3j1t (middle), and 3j2t (lower). The vertical lines on the points and the hatched bands show the experimental and fit uncertainties, respectively. The expected distribution from the STq,b+STb,q processes (multiplied by a factor of 1000) is shown by the solid blue line. The lower panels show the ratio of the data to the fit.

Distribution of the multivariate discriminators, comparing data to simulation normalised after the fit procedure, for the muon channel on the left and for the electron channel on the right, for 2j1t (upper), 3j1t (middle), and 3j2t (lower). The vertical lines on the points and the hatched bands show the experimental and fit uncertainties, respectively. The expected distribution from the STq,b+STb,q processes (multiplied by a factor of 1000) is shown by the solid blue line. The lower panels show the ratio of the data to the fit.

Distribution of the multivariate discriminators, comparing data to simulation normalised after the fit procedure, for the muon channel on the left and for the electron channel on the right, for 2j1t (upper), 3j1t (middle), and 3j2t (lower). The vertical lines on the points and the hatched bands show the experimental and fit uncertainties, respectively. The expected distribution from the STq,b+STb,q processes (multiplied by a factor of 1000) is shown by the solid blue line. The lower panels show the ratio of the data to the fit.

Distribution of the multivariate discriminators, comparing data to simulation normalised after the fit procedure, for the muon channel on the left and for the electron channel on the right, for 2j1t (upper), 3j1t (middle), and 3j2t (lower). The vertical lines on the points and the hatched bands show the experimental and fit uncertainties, respectively. The expected distribution from the STq,b+STb,q processes (multiplied by a factor of 1000) is shown by the solid blue line. The lower panels show the ratio of the data to the fit.

Values of the third-row elements of the CKM matrix inferred from low-energy measurements with the respective values of the top quark decay branching fractions. The q in bs{V_{tq}} and \mathcal{B}(t o Wq) in the first column refers to b, s, and d quarks, according to the quark label shown in the header row.

For each of the production and decay vertices, the cross section times branching fraction for the corresponding signal process from simulation. The uncertainties shown includethose from the factorisation and renormalisation scales, the PDFs, and any experimental uncer-tainties, where appropriate.

The sources and relative values in percent of the systematic uncertainty in the measurement of the STb,b cross section. The uncertainties are broken up into profiled and nonprofiled sources.

The signal strengths obtained under SM assumptions.

Results obtained under SM assumptions.

Results obtained under first BSM scenario.

Results obtained under second BSM scenario.

The expected and observed 95% CL upper limits on the product of cross section and branching fraction for direct production of charginos as a function of chargino mass, for a chargino lifetime of 3.3 ns and with a purely wino LSP. The branching fraction for $\widetilde{\chi}^{\pm}_{1} \rightarrow \widetilde{\chi}^{0}_{1} \pi^{\pm}$ is set to 100%. Shown are the full Run 2 results, derived from the results of the search in the 2017 and 2018 data sets combined with those of the previous CMS result obtained in the 2015 and 2016 data sets. The cross section includes both $\widetilde{\chi}^{\pm}_{1} \widetilde{\chi}^{0}_{1}$ and $\widetilde{\chi}^{\pm}_{1}\widetilde{\chi}^{\mp}_{1}$ production in roughly a 2:1 ratio for all chargino masses considered. The dashed line indicates the theoretical prediction.

The expected and observed 95% CL upper limits on the product of cross section and branching fraction for direct production of charginos as a function of chargino mass, for a chargino lifetime of 33 ns and with a purely wino LSP. The branching fraction for $\widetilde{\chi}^{\pm}_{1} \rightarrow \widetilde{\chi}^{0}_{1} \pi^{\pm}$ is set to 100%. Shown are the full Run 2 results, derived from the results of the search in the 2017 and 2018 data sets combined with those of the previous CMS result obtained in the 2015 and 2016 data sets. The cross section includes both $\widetilde{\chi}^{\pm}_{1} \widetilde{\chi}^{0}_{1}$ and $\widetilde{\chi}^{\pm}_{1}\widetilde{\chi}^{\mp}_{1}$ production in roughly a 2:1 ratio for all chargino masses considered. The dashed line indicates the theoretical prediction.

The expected and observed 95% CL upper limits on the product of cross section and branching fraction for direct production of charginos as a function of chargino mass, for a chargino lifetime of 33 ns and with a purely wino LSP. The branching fraction for $\widetilde{\chi}^{\pm}_{1} \rightarrow \widetilde{\chi}^{0}_{1} \pi^{\pm}$ is set to 100%. Shown are the full Run 2 results, derived from the results of the search in the 2017 and 2018 data sets combined with those of the previous CMS result obtained in the 2015 and 2016 data sets. The cross section includes both $\widetilde{\chi}^{\pm}_{1} \widetilde{\chi}^{0}_{1}$ and $\widetilde{\chi}^{\pm}_{1}\widetilde{\chi}^{\mp}_{1}$ production in roughly a 2:1 ratio for all chargino masses considered. The dashed line indicates the theoretical prediction.

The expected and observed 95% CL upper limits on the product of cross section and branching fraction for direct production of charginos as a function of chargino mass, for a chargino lifetime of 333 ns and with a purely wino LSP. The branching fraction for $\widetilde{\chi}^{\pm}_{1} \rightarrow \widetilde{\chi}^{0}_{1} \pi^{\pm}$ is set to 100%. Shown are the full Run 2 results, derived from the results of the search in the 2017 and 2018 data sets combined with those of the previous CMS result obtained in the 2015 and 2016 data sets. The cross section includes both $\widetilde{\chi}^{\pm}_{1} \widetilde{\chi}^{0}_{1}$ and $\widetilde{\chi}^{\pm}_{1}\widetilde{\chi}^{\mp}_{1}$ production in roughly a 2:1 ratio for all chargino masses considered. The dashed line indicates the theoretical prediction.

The expected and observed 95% CL upper limits on the product of cross section and branching fraction for direct production of charginos as a function of chargino mass, for a chargino lifetime of 333 ns and with a purely wino LSP. The branching fraction for $\widetilde{\chi}^{\pm}_{1} \rightarrow \widetilde{\chi}^{0}_{1} \pi^{\pm}$ is set to 100%. Shown are the full Run 2 results, derived from the results of the search in the 2017 and 2018 data sets combined with those of the previous CMS result obtained in the 2015 and 2016 data sets. The cross section includes both $\widetilde{\chi}^{\pm}_{1} \widetilde{\chi}^{0}_{1}$ and $\widetilde{\chi}^{\pm}_{1}\widetilde{\chi}^{\mp}_{1}$ production in roughly a 2:1 ratio for all chargino masses considered. The dashed line indicates the theoretical prediction.

The expected and observed 95% CL upper limits on the product of cross section and branching fraction for direct production of charginos as a function of chargino mass, for a chargino lifetime of 0.3 ns and with a purely higgsino LSP. The branching fractions are set to 95.5% for $\widetilde{\chi}^{\pm}_{1} \rightarrow \widetilde{\chi}^{0}_{1,2} \pi^{\pm}$, 3% for $\widetilde{\chi}^{-}_{1} \rightarrow \widetilde{\chi}^{0}_{1,2} e\nu$, and 1.5% for $\widetilde{\chi}^{-}_{1} \rightarrow \widetilde{\chi}^{0}_{1,2} \mu\nu$, with equal branching fractions and production cross sections between $\widetilde{\chi}^{0}_{1}$ and $\widetilde{\chi}^{0}_{2}$. The cross section includes both $\widetilde{\chi}^{\pm}_{1} \widetilde{\chi}^{0}_{1,2}$ and $\widetilde{\chi}^{\pm}_{1}\widetilde{\chi}^{\mp}_{1}$ production in roughly a 7:2 ratio for all chargino masses considered. The dashed line indicates the theoretical prediction.

The expected and observed 95% CL upper limits on the product of cross section and branching fraction for direct production of charginos as a function of chargino mass, for a chargino lifetime of 0.3 ns and with a purely higgsino LSP. The branching fractions are set to 95.5% for $\widetilde{\chi}^{\pm}_{1} \rightarrow \widetilde{\chi}^{0}_{1,2} \pi^{\pm}$, 3% for $\widetilde{\chi}^{-}_{1} \rightarrow \widetilde{\chi}^{0}_{1,2} e\nu$, and 1.5% for $\widetilde{\chi}^{-}_{1} \rightarrow \widetilde{\chi}^{0}_{1,2} \mu\nu$, with equal branching fractions and production cross sections between $\widetilde{\chi}^{0}_{1}$ and $\widetilde{\chi}^{0}_{2}$. The cross section includes both $\widetilde{\chi}^{\pm}_{1} \widetilde{\chi}^{0}_{1,2}$ and $\widetilde{\chi}^{\pm}_{1}\widetilde{\chi}^{\mp}_{1}$ production in roughly a 7:2 ratio for all chargino masses considered. The dashed line indicates the theoretical prediction.

The expected and observed 95% CL upper limits on the product of cross section and branching fraction for direct production of charginos as a function of chargino mass, for a chargino lifetime of 3.3 ns and with a purely higgsino LSP. The branching fractions are set to 95.5% for $\widetilde{\chi}^{\pm}_{1} \rightarrow \widetilde{\chi}^{0}_{1,2} \pi^{\pm}$, 3% for $\widetilde{\chi}^{-}_{1} \rightarrow \widetilde{\chi}^{0}_{1,2} e\nu$, and 1.5% for $\widetilde{\chi}^{-}_{1} \rightarrow \widetilde{\chi}^{0}_{1,2} \mu\nu$, with equal branching fractions and production cross sections between $\widetilde{\chi}^{0}_{1}$ and $\widetilde{\chi}^{0}_{2}$. The cross section includes both $\widetilde{\chi}^{\pm}_{1} \widetilde{\chi}^{0}_{1,2}$ and $\widetilde{\chi}^{\pm}_{1}\widetilde{\chi}^{\mp}_{1}$ production in roughly a 7:2 ratio for all chargino masses considered. The dashed line indicates the theoretical prediction.

The expected and observed 95% CL upper limits on the product of cross section and branching fraction for direct production of charginos as a function of chargino mass, for a chargino lifetime of 3.3 ns and with a purely higgsino LSP. The branching fractions are set to 95.5% for $\widetilde{\chi}^{\pm}_{1} \rightarrow \widetilde{\chi}^{0}_{1,2} \pi^{\pm}$, 3% for $\widetilde{\chi}^{-}_{1} \rightarrow \widetilde{\chi}^{0}_{1,2} e\nu$, and 1.5% for $\widetilde{\chi}^{-}_{1} \rightarrow \widetilde{\chi}^{0}_{1,2} \mu\nu$, with equal branching fractions and production cross sections between $\widetilde{\chi}^{0}_{1}$ and $\widetilde{\chi}^{0}_{2}$. The cross section includes both $\widetilde{\chi}^{\pm}_{1} \widetilde{\chi}^{0}_{1,2}$ and $\widetilde{\chi}^{\pm}_{1}\widetilde{\chi}^{\mp}_{1}$ production in roughly a 7:2 ratio for all chargino masses considered. The dashed line indicates the theoretical prediction.

The expected and observed 95% CL upper limits on the product of cross section and branching fraction for direct production of charginos as a function of chargino mass, for a chargino lifetime of 33 ns and with a purely higgsino LSP. The branching fractions are set to 95.5% for $\widetilde{\chi}^{\pm}_{1} \rightarrow \widetilde{\chi}^{0}_{1,2} \pi^{\pm}$, 3% for $\widetilde{\chi}^{-}_{1} \rightarrow \widetilde{\chi}^{0}_{1,2} e\nu$, and 1.5% for $\widetilde{\chi}^{-}_{1} \rightarrow \widetilde{\chi}^{0}_{1,2} \mu\nu$, with equal branching fractions and production cross sections between $\widetilde{\chi}^{0}_{1}$ and $\widetilde{\chi}^{0}_{2}$. The cross section includes both $\widetilde{\chi}^{\pm}_{1} \widetilde{\chi}^{0}_{1,2}$ and $\widetilde{\chi}^{\pm}_{1}\widetilde{\chi}^{\mp}_{1}$ production in roughly a 7:2 ratio for all chargino masses considered. The dashed line indicates the theoretical prediction.

The expected and observed 95% CL upper limits on the product of cross section and branching fraction for direct production of charginos as a function of chargino mass, for a chargino lifetime of 33 ns and with a purely higgsino LSP. The branching fractions are set to 95.5% for $\widetilde{\chi}^{\pm}_{1} \rightarrow \widetilde{\chi}^{0}_{1,2} \pi^{\pm}$, 3% for $\widetilde{\chi}^{-}_{1} \rightarrow \widetilde{\chi}^{0}_{1,2} e\nu$, and 1.5% for $\widetilde{\chi}^{-}_{1} \rightarrow \widetilde{\chi}^{0}_{1,2} \mu\nu$, with equal branching fractions and production cross sections between $\widetilde{\chi}^{0}_{1}$ and $\widetilde{\chi}^{0}_{2}$. The cross section includes both $\widetilde{\chi}^{\pm}_{1} \widetilde{\chi}^{0}_{1,2}$ and $\widetilde{\chi}^{\pm}_{1}\widetilde{\chi}^{\mp}_{1}$ production in roughly a 7:2 ratio for all chargino masses considered. The dashed line indicates the theoretical prediction.

The expected and observed 95% CL upper limits on the product of cross section and branching fraction for direct production of charginos as a function of chargino mass, for a chargino lifetime of 333 ns and with a purely higgsino LSP. The branching fractions are set to 95.5% for $\widetilde{\chi}^{\pm}_{1} \rightarrow \widetilde{\chi}^{0}_{1,2} \pi^{\pm}$, 3% for $\widetilde{\chi}^{-}_{1} \rightarrow \widetilde{\chi}^{0}_{1,2} e\nu$, and 1.5% for $\widetilde{\chi}^{-}_{1} \rightarrow \widetilde{\chi}^{0}_{1,2} \mu\nu$, with equal branching fractions and production cross sections between $\widetilde{\chi}^{0}_{1}$ and $\widetilde{\chi}^{0}_{2}$. The cross section includes both $\widetilde{\chi}^{\pm}_{1} \widetilde{\chi}^{0}_{1,2}$ and $\widetilde{\chi}^{\pm}_{1}\widetilde{\chi}^{\mp}_{1}$ production in roughly a 7:2 ratio for all chargino masses considered. The dashed line indicates the theoretical prediction.

The expected and observed 95% CL upper limits on the product of cross section and branching fraction for direct production of charginos as a function of chargino mass, for a chargino lifetime of 333 ns and with a purely higgsino LSP. The branching fractions are set to 95.5% for $\widetilde{\chi}^{\pm}_{1} \rightarrow \widetilde{\chi}^{0}_{1,2} \pi^{\pm}$, 3% for $\widetilde{\chi}^{-}_{1} \rightarrow \widetilde{\chi}^{0}_{1,2} e\nu$, and 1.5% for $\widetilde{\chi}^{-}_{1} \rightarrow \widetilde{\chi}^{0}_{1,2} \mu\nu$, with equal branching fractions and production cross sections between $\widetilde{\chi}^{0}_{1}$ and $\widetilde{\chi}^{0}_{2}$. The cross section includes both $\widetilde{\chi}^{\pm}_{1} \widetilde{\chi}^{0}_{1,2}$ and $\widetilde{\chi}^{\pm}_{1}\widetilde{\chi}^{\mp}_{1}$ production in roughly a 7:2 ratio for all chargino masses considered. The dashed line indicates the theoretical prediction.

The expected and observed constraints on chargino lifetime and mass for a purely wino LSP in the context of AMSB, where the chargino lifetime is explicitly varied. The chargino branching fraction is set to 100% for $\widetilde{\chi}^{\pm}_{1} \rightarrow \widetilde{\chi}^{0}_{1} \pi^{\pm}$. Shown are the full Run 2 results, derived from the results of the search in the 2017 and 2018 data sets combined with those of the previous CMS result obtained in the 2015 and 2016 data sets. The region to the left of the curve is excluded at 95% CL. The prediction from PLB 721 (2013) 252 is indicated in the dashed line.

The expected and observed constraints on chargino lifetime and mass for a purely wino LSP in the context of AMSB, where the chargino lifetime is explicitly varied. The chargino branching fraction is set to 100% for $\widetilde{\chi}^{\pm}_{1} \rightarrow \widetilde{\chi}^{0}_{1} \pi^{\pm}$. Shown are the full Run 2 results, derived from the results of the search in the 2017 and 2018 data sets combined with those of the previous CMS result obtained in the 2015 and 2016 data sets. The region to the left of the curve is excluded at 95% CL. The prediction from PLB 721 (2013) 252 is indicated in the dashed line.

The expected and observed 95% CL upper limits on the product of cross section and branching fraction for direct production of charginos as a function of chargino mass and mean proper lifetime, with a purely wino LSP. The branching fraction for $\widetilde{\chi}^{\pm}_{1} \rightarrow \widetilde{\chi}^{0}_{1} \pi^{\pm}$ is set to 100%. Shown are the full Run 2 results, derived from the results of the search in the 2017 and 2018 data sets combined with those of the previous CMS result obtained in the 2015 and 2016 data sets. The cross section includes both $\widetilde{\chi}^{\pm}_{1} \widetilde{\chi}^{0}_{1}$ and $\widetilde{\chi}^{\pm}_{1}\widetilde{\chi}^{\mp}_{1}$ production in roughly a 2:1 ratio for all chargino masses considered.

The expected and observed 95% CL upper limits on the product of cross section and branching fraction for direct production of charginos as a function of chargino mass and mean proper lifetime, with a purely wino LSP. The branching fraction for $\widetilde{\chi}^{\pm}_{1} \rightarrow \widetilde{\chi}^{0}_{1} \pi^{\pm}$ is set to 100%. Shown are the full Run 2 results, derived from the results of the search in the 2017 and 2018 data sets combined with those of the previous CMS result obtained in the 2015 and 2016 data sets. The cross section includes both $\widetilde{\chi}^{\pm}_{1} \widetilde{\chi}^{0}_{1}$ and $\widetilde{\chi}^{\pm}_{1}\widetilde{\chi}^{\mp}_{1}$ production in roughly a 2:1 ratio for all chargino masses considered.

The expected and observed constraints on chargino lifetime and mass for a purely higgsino LSP in the context of AMSB, where the chargino lifetime is explicitly varied. The chargino branching fraction is set to 95.5% for $\widetilde{\chi}^{\pm}_{1} \rightarrow \widetilde{\chi}^{0}_{1,2} \pi^{\pm}$, 3% for $\widetilde{\chi}^{-}_{1} \rightarrow \widetilde{\chi}^{0}_{1,2} e\nu$, and 1.5% for $\widetilde{\chi}^{-}_{1} \rightarrow \widetilde{\chi}^{0}_{1,2} \mu\nu$, with equal branching fractions and production cross sections between $\widetilde{\chi}^{0}_{1}$ and $\widetilde{\chi}^{0}_{2}$. The region to the left of the curve is excluded at 95% CL. The prediction from Phys. Lett. B 781 (2018) 306 is indicated in the dashed line.

The expected and observed constraints on chargino lifetime and mass for a purely higgsino LSP in the context of AMSB, where the chargino lifetime is explicitly varied. The chargino branching fraction is set to 95.5% for $\widetilde{\chi}^{\pm}_{1} \rightarrow \widetilde{\chi}^{0}_{1,2} \pi^{\pm}$, 3% for $\widetilde{\chi}^{-}_{1} \rightarrow \widetilde{\chi}^{0}_{1,2} e\nu$, and 1.5% for $\widetilde{\chi}^{-}_{1} \rightarrow \widetilde{\chi}^{0}_{1,2} \mu\nu$, with equal branching fractions and production cross sections between $\widetilde{\chi}^{0}_{1}$ and $\widetilde{\chi}^{0}_{2}$. The region to the left of the curve is excluded at 95% CL. The prediction from Phys. Lett. B 781 (2018) 306 is indicated in the dashed line.

The expected and observed 95% CL upper limits on the product of cross section and branching fraction for direct production of charginos as a function of chargino mass and mean proper lifetime, with a purely higgsino LSP. The branching fractions are set to 95.5% for $\widetilde{\chi}^{\pm}_{1} \rightarrow \widetilde{\chi}^{0}_{1,2} \pi^{\pm}$, 3% for $\widetilde{\chi}^{-}_{1} \rightarrow \widetilde{\chi}^{0}_{1,2} e\nu$, and 1.5% for $\widetilde{\chi}^{-}_{1} \rightarrow \widetilde{\chi}^{0}_{1,2} \mu\nu$, with equal branching fractions and production cross sections between $\widetilde{\chi}^{0}_{1}$ and $\widetilde{\chi}^{0}_{2}$. The cross section includes both $\widetilde{\chi}^{\pm}_{1} \widetilde{\chi}^{0}_{1,2}$ and $\widetilde{\chi}^{\pm}_{1}\widetilde{\chi}^{\mp}_{1}$ production in roughly a 7:2 ratio for all chargino masses considered.

The expected and observed 95% CL upper limits on the product of cross section and branching fraction for direct production of charginos as a function of chargino mass and mean proper lifetime, with a purely higgsino LSP. The branching fractions are set to 95.5% for $\widetilde{\chi}^{\pm}_{1} \rightarrow \widetilde{\chi}^{0}_{1,2} \pi^{\pm}$, 3% for $\widetilde{\chi}^{-}_{1} \rightarrow \widetilde{\chi}^{0}_{1,2} e\nu$, and 1.5% for $\widetilde{\chi}^{-}_{1} \rightarrow \widetilde{\chi}^{0}_{1,2} \mu\nu$, with equal branching fractions and production cross sections between $\widetilde{\chi}^{0}_{1}$ and $\widetilde{\chi}^{0}_{2}$. The cross section includes both $\widetilde{\chi}^{\pm}_{1} \widetilde{\chi}^{0}_{1,2}$ and $\widetilde{\chi}^{\pm}_{1}\widetilde{\chi}^{\mp}_{1}$ production in roughly a 7:2 ratio for all chargino masses considered.

Predicted signal yields for the 2017 data-taking period, corresponding to $41.5\,\text{fb}^{-1}$, after the application of each search requirement for three chargino lifetime hypotheses ($\tau = 0.3$, $3.3$, and $33\,\text{ns}{}$) with a chargino mass of $700\,\text{GeV}{}$ in the case of a purely wino neutralino LSP. Excepting the final three, the requirements listed are cumulative such that only the events and objects passing a given requirement are considered in subsequent requirements. In the case of the final three requirements on the number of tracker layers with measurement, these are exclusive signal category selections where only one is applied for each category. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Predicted signal yields for the 2017 data-taking period, corresponding to $41.5\,\text{fb}^{-1}$, after the application of each search requirement for three chargino lifetime hypotheses ($\tau = 0.3$, $3.3$, and $33\,\text{ns}{}$) with a chargino mass of $700\,\text{GeV}{}$ in the case of a purely wino neutralino LSP. Excepting the final three, the requirements listed are cumulative such that only the events and objects passing a given requirement are considered in subsequent requirements. In the case of the final three requirements on the number of tracker layers with measurement, these are exclusive signal category selections where only one is applied for each category. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Predicted signal yields for the 2017 data-taking period, corresponding to $41.5\,\text{fb}^{-1}$, after the application of each search requirement for three chargino lifetime hypotheses ($\tau = 0.3$, $3.3$, and $33\,\text{ns}{}$) with a chargino mass of $700\,\text{GeV}{}$ in the case of a purely higgsino neutralino LSP. Excepting the final three, the requirements listed are cumulative such that only the events and objects passing a given requirement are considered in subsequent requirements. In the case of the final three requirements on the number of tracker layers with measurement, these are exclusive signal category selections where only one is applied for each category. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Predicted signal yields for the 2017 data-taking period, corresponding to $41.5\,\text{fb}^{-1}$, after the application of each search requirement for three chargino lifetime hypotheses ($\tau = 0.3$, $3.3$, and $33\,\text{ns}{}$) with a chargino mass of $700\,\text{GeV}{}$ in the case of a purely higgsino neutralino LSP. Excepting the final three, the requirements listed are cumulative such that only the events and objects passing a given requirement are considered in subsequent requirements. In the case of the final three requirements on the number of tracker layers with measurement, these are exclusive signal category selections where only one is applied for each category. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Predicted signal yields for the 2017 data-taking period, corresponding to $41.5\,\text{fb}^{-1}$, after the application of each search requirement for three chargino lifetime hypotheses ($\tau = 0.3$, $3.3$, and $33\,\text{ns}{}$) with a chargino mass of $300\,\text{GeV}{}$ in the case of a purely wino neutralino LSP. Excepting the final three, the requirements listed are cumulative such that only the events and objects passing a given requirement are considered in subsequent requirements. In the case of the final three requirements on the number of tracker layers with measurement, these are exclusive signal category selections where only one is applied for each category. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Predicted signal yields for the 2017 data-taking period, corresponding to $41.5\,\text{fb}^{-1}$, after the application of each search requirement for three chargino lifetime hypotheses ($\tau = 0.3$, $3.3$, and $33\,\text{ns}{}$) with a chargino mass of $300\,\text{GeV}{}$ in the case of a purely wino neutralino LSP. Excepting the final three, the requirements listed are cumulative such that only the events and objects passing a given requirement are considered in subsequent requirements. In the case of the final three requirements on the number of tracker layers with measurement, these are exclusive signal category selections where only one is applied for each category. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Predicted signal yields for the 2017 data-taking period, corresponding to $41.5\,\text{fb}^{-1}$, after the application of each search requirement for three chargino lifetime hypotheses ($\tau = 0.3$, $3.3$, and $33\,\text{ns}{}$) with a chargino mass of $300\,\text{GeV}{}$ in the case of a purely higgsino neutralino LSP. Excepting the final three, the requirements listed are cumulative such that only the events and objects passing a given requirement are considered in subsequent requirements. In the case of the final three requirements on the number of tracker layers with measurement, these are exclusive signal category selections where only one is applied for each category. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Predicted signal yields for the 2017 data-taking period, corresponding to $41.5\,\text{fb}^{-1}$, after the application of each search requirement for three chargino lifetime hypotheses ($\tau = 0.3$, $3.3$, and $33\,\text{ns}{}$) with a chargino mass of $300\,\text{GeV}{}$ in the case of a purely higgsino neutralino LSP. Excepting the final three, the requirements listed are cumulative such that only the events and objects passing a given requirement are considered in subsequent requirements. In the case of the final three requirements on the number of tracker layers with measurement, these are exclusive signal category selections where only one is applied for each category. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Predicted signal yields for the 2018A data-taking period, corresponding to $21.1\,\text{fb}^{-1}$, after the application of each search requirement for three chargino lifetime hypotheses ($\tau = 0.3$, $3.3$, and $33\,\text{ns}{}$) with a chargino mass of $700\,\text{GeV}{}$ in the case of a purely wino neutralino LSP. Excepting the final three, the requirements listed are cumulative such that only the events and objects passing a given requirement are considered in subsequent requirements. In the case of the final three requirements on the number of tracker layers with measurement, these are exclusive signal category selections where only one is applied for each category. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Predicted signal yields for the 2018A data-taking period, corresponding to $21.1\,\text{fb}^{-1}$, after the application of each search requirement for three chargino lifetime hypotheses ($\tau = 0.3$, $3.3$, and $33\,\text{ns}{}$) with a chargino mass of $700\,\text{GeV}{}$ in the case of a purely wino neutralino LSP. Excepting the final three, the requirements listed are cumulative such that only the events and objects passing a given requirement are considered in subsequent requirements. In the case of the final three requirements on the number of tracker layers with measurement, these are exclusive signal category selections where only one is applied for each category. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Predicted signal yields for the 2018A data-taking period, corresponding to $21.1\,\text{fb}^{-1}$, after the application of each search requirement for three chargino lifetime hypotheses ($\tau = 0.3$, $3.3$, and $33\,\text{ns}{}$) with a chargino mass of $700\,\text{GeV}{}$ in the case of a purely higgsino neutralino LSP. Excepting the final three, the requirements listed are cumulative such that only the events and objects passing a given requirement are considered in subsequent requirements. In the case of the final three requirements on the number of tracker layers with measurement, these are exclusive signal category selections where only one is applied for each category. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Predicted signal yields for the 2018A data-taking period, corresponding to $21.1\,\text{fb}^{-1}$, after the application of each search requirement for three chargino lifetime hypotheses ($\tau = 0.3$, $3.3$, and $33\,\text{ns}{}$) with a chargino mass of $700\,\text{GeV}{}$ in the case of a purely higgsino neutralino LSP. Excepting the final three, the requirements listed are cumulative such that only the events and objects passing a given requirement are considered in subsequent requirements. In the case of the final three requirements on the number of tracker layers with measurement, these are exclusive signal category selections where only one is applied for each category. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Predicted signal yields for the 2018A data-taking period, corresponding to $21.1\,\text{fb}^{-1}$, after the application of each search requirement for three chargino lifetime hypotheses ($\tau = 0.3$, $3.3$, and $33\,\text{ns}{}$) with a chargino mass of $300\,\text{GeV}{}$ in the case of a purely wino neutralino LSP. Excepting the final three, the requirements listed are cumulative such that only the events and objects passing a given requirement are considered in subsequent requirements. In the case of the final three requirements on the number of tracker layers with measurement, these are exclusive signal category selections where only one is applied for each category. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Predicted signal yields for the 2018A data-taking period, corresponding to $21.1\,\text{fb}^{-1}$, after the application of each search requirement for three chargino lifetime hypotheses ($\tau = 0.3$, $3.3$, and $33\,\text{ns}{}$) with a chargino mass of $300\,\text{GeV}{}$ in the case of a purely wino neutralino LSP. Excepting the final three, the requirements listed are cumulative such that only the events and objects passing a given requirement are considered in subsequent requirements. In the case of the final three requirements on the number of tracker layers with measurement, these are exclusive signal category selections where only one is applied for each category. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Predicted signal yields for the 2018A data-taking period, corresponding to $21.1\,\text{fb}^{-1}$, after the application of each search requirement for three chargino lifetime hypotheses ($\tau = 0.3$, $3.3$, and $33\,\text{ns}{}$) with a chargino mass of $300\,\text{GeV}{}$ in the case of a purely higgsino neutralino LSP. Excepting the final three, the requirements listed are cumulative such that only the events and objects passing a given requirement are considered in subsequent requirements. In the case of the final three requirements on the number of tracker layers with measurement, these are exclusive signal category selections where only one is applied for each category. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Predicted signal yields for the 2018A data-taking period, corresponding to $21.1\,\text{fb}^{-1}$, after the application of each search requirement for three chargino lifetime hypotheses ($\tau = 0.3$, $3.3$, and $33\,\text{ns}{}$) with a chargino mass of $300\,\text{GeV}{}$ in the case of a purely higgsino neutralino LSP. Excepting the final three, the requirements listed are cumulative such that only the events and objects passing a given requirement are considered in subsequent requirements. In the case of the final three requirements on the number of tracker layers with measurement, these are exclusive signal category selections where only one is applied for each category. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Predicted signal yields for the 2018B data-taking period, corresponding to $38.6\,\text{fb}^{-1}$, after the application of each search requirement for three chargino lifetime hypotheses ($\tau = 0.3$, $3.3$, and $33\,\text{ns}{}$) with a chargino mass of $700\,\text{GeV}{}$ in the case of a purely wino neutralino LSP. Excepting the final three, the requirements listed are cumulative such that only the events and objects passing a given requirement are considered in subsequent requirements. In the case of the final three requirements on the number of tracker layers with measurement, these are exclusive signal category selections where only one is applied for each category. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Predicted signal yields for the 2018B data-taking period, corresponding to $38.6\,\text{fb}^{-1}$, after the application of each search requirement for three chargino lifetime hypotheses ($\tau = 0.3$, $3.3$, and $33\,\text{ns}{}$) with a chargino mass of $700\,\text{GeV}{}$ in the case of a purely wino neutralino LSP. Excepting the final three, the requirements listed are cumulative such that only the events and objects passing a given requirement are considered in subsequent requirements. In the case of the final three requirements on the number of tracker layers with measurement, these are exclusive signal category selections where only one is applied for each category. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Predicted signal yields for the 2018B data-taking period, corresponding to $38.6\,\text{fb}^{-1}$, after the application of each search requirement for three chargino lifetime hypotheses ($\tau = 0.3$, $3.3$, and $33\,\text{ns}{}$) with a chargino mass of $700\,\text{GeV}{}$ in the case of a purely higgsino neutralino LSP. Excepting the final three, the requirements listed are cumulative such that only the events and objects passing a given requirement are considered in subsequent requirements. In the case of the final three requirements on the number of tracker layers with measurement, these are exclusive signal category selections where only one is applied for each category. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Predicted signal yields for the 2018B data-taking period, corresponding to $38.6\,\text{fb}^{-1}$, after the application of each search requirement for three chargino lifetime hypotheses ($\tau = 0.3$, $3.3$, and $33\,\text{ns}{}$) with a chargino mass of $700\,\text{GeV}{}$ in the case of a purely higgsino neutralino LSP. Excepting the final three, the requirements listed are cumulative such that only the events and objects passing a given requirement are considered in subsequent requirements. In the case of the final three requirements on the number of tracker layers with measurement, these are exclusive signal category selections where only one is applied for each category. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Predicted signal yields for the 2018B data-taking period, corresponding to $38.6\,\text{fb}^{-1}$, after the application of each search requirement for three chargino lifetime hypotheses ($\tau = 0.3$, $3.3$, and $33\,\text{ns}{}$) with a chargino mass of $300\,\text{GeV}{}$ in the case of a purely wino neutralino LSP. Excepting the final three, the requirements listed are cumulative such that only the events and objects passing a given requirement are considered in subsequent requirements. In the case of the final three requirements on the number of tracker layers with measurement, these are exclusive signal category selections where only one is applied for each category. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Predicted signal yields for the 2018B data-taking period, corresponding to $38.6\,\text{fb}^{-1}$, after the application of each search requirement for three chargino lifetime hypotheses ($\tau = 0.3$, $3.3$, and $33\,\text{ns}{}$) with a chargino mass of $300\,\text{GeV}{}$ in the case of a purely wino neutralino LSP. Excepting the final three, the requirements listed are cumulative such that only the events and objects passing a given requirement are considered in subsequent requirements. In the case of the final three requirements on the number of tracker layers with measurement, these are exclusive signal category selections where only one is applied for each category. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Predicted signal yields for the 2018B data-taking period, corresponding to $38.6\,\text{fb}^{-1}$, after the application of each search requirement for three chargino lifetime hypotheses ($\tau = 0.3$, $3.3$, and $33\,\text{ns}{}$) with a chargino mass of $300\,\text{GeV}{}$ in the case of a purely higgsino neutralino LSP. Excepting the final three, the requirements listed are cumulative such that only the events and objects passing a given requirement are considered in subsequent requirements. In the case of the final three requirements on the number of tracker layers with measurement, these are exclusive signal category selections where only one is applied for each category. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Predicted signal yields for the 2018B data-taking period, corresponding to $38.6\,\text{fb}^{-1}$, after the application of each search requirement for three chargino lifetime hypotheses ($\tau = 0.3$, $3.3$, and $33\,\text{ns}{}$) with a chargino mass of $300\,\text{GeV}{}$ in the case of a purely higgsino neutralino LSP. Excepting the final three, the requirements listed are cumulative such that only the events and objects passing a given requirement are considered in subsequent requirements. In the case of the final three requirements on the number of tracker layers with measurement, these are exclusive signal category selections where only one is applied for each category. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Signal acceptance times efficiency ($A\times\epsilon$) for each of the generated chargino masses and lifetimes for $\mathrm{p}\mathrm{p} \rightarrow \widetilde{\chi}^\pm_{1} \widetilde{\chi}^\mp_{1}$ events, in the case of a purely wino neutralino LSP. The denominator for the acceptance is the total number of $\widetilde{\chi}^\pm_{1} \widetilde{\chi}^\mp_{1}$ events generated, while the numerator is the number of those events that are selected by the signal selection after being processed with the same reconstruction software used on the data. These $A\times\epsilon$ values correspond to the conditions simulated for the 2017 data-taking period. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Signal acceptance times efficiency ($A\times\epsilon$) for each of the generated chargino masses and lifetimes for $\mathrm{p}\mathrm{p} \rightarrow \widetilde{\chi}^\pm_{1} \widetilde{\chi}^\mp_{1}$ events, in the case of a purely wino neutralino LSP. The denominator for the acceptance is the total number of $\widetilde{\chi}^\pm_{1} \widetilde{\chi}^\mp_{1}$ events generated, while the numerator is the number of those events that are selected by the signal selection after being processed with the same reconstruction software used on the data. These $A\times\epsilon$ values correspond to the conditions simulated for the 2017 data-taking period. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Signal acceptance times efficiency ($A\times\epsilon$) for each of the generated chargino masses and lifetimes for $\mathrm{p}\mathrm{p} \rightarrow \widetilde{\chi}^\pm_{1} \widetilde{\chi}^0_{1}$ events, in the case of a purely wino neutralino LSP. The denominator for the acceptance is the total number of $\widetilde{\chi}^\pm_{1} \widetilde{\chi}^0_{1}$ events generated, while the numerator is the number of those events that are selected by the signal selection after being processed with the same reconstruction software used on the data. These $A\times\epsilon$ values correspond to the conditions simulated for the 2017 data-taking period. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Signal acceptance times efficiency ($A\times\epsilon$) for each of the generated chargino masses and lifetimes for $\mathrm{p}\mathrm{p} \rightarrow \widetilde{\chi}^\pm_{1} \widetilde{\chi}^0_{1}$ events, in the case of a purely wino neutralino LSP. The denominator for the acceptance is the total number of $\widetilde{\chi}^\pm_{1} \widetilde{\chi}^0_{1}$ events generated, while the numerator is the number of those events that are selected by the signal selection after being processed with the same reconstruction software used on the data. These $A\times\epsilon$ values correspond to the conditions simulated for the 2017 data-taking period. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Signal acceptance times efficiency ($A\times\epsilon$) for each of the generated chargino masses and lifetimes for $\mathrm{p}\mathrm{p} \rightarrow \widetilde{\chi}^\pm_{1} \widetilde{\chi}^\mp_{1}$ events, in the case of a purely higgsino neutralino LSP. The denominator for the acceptance is the total number of $\widetilde{\chi}^\pm_{1} \widetilde{\chi}^\mp_{1}$ events generated, while the numerator is the number of those events that are selected by the signal selection after being processed with the same reconstruction software used on the data. These $A\times\epsilon$ values correspond to the conditions simulated for the 2017 data-taking period. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Signal acceptance times efficiency ($A\times\epsilon$) for each of the generated chargino masses and lifetimes for $\mathrm{p}\mathrm{p} \rightarrow \widetilde{\chi}^\pm_{1} \widetilde{\chi}^\mp_{1}$ events, in the case of a purely higgsino neutralino LSP. The denominator for the acceptance is the total number of $\widetilde{\chi}^\pm_{1} \widetilde{\chi}^\mp_{1}$ events generated, while the numerator is the number of those events that are selected by the signal selection after being processed with the same reconstruction software used on the data. These $A\times\epsilon$ values correspond to the conditions simulated for the 2017 data-taking period. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Signal acceptance times efficiency ($A\times\epsilon$) for each of the generated chargino masses and lifetimes for $\mathrm{p}\mathrm{p} \rightarrow \widetilde{\chi}^\pm_{1} \widetilde{\chi}^0_{1,2}$ events, in the case of a purely higgsino neutralino LSP. The denominator for the acceptance is the total number of $\widetilde{\chi}^\pm_{1} \widetilde{\chi}^0_{1,2}$ events generated, while the numerator is the number of those events that are selected by the signal selection after being processed with the same reconstruction software used on the data. These $A\times\epsilon$ values correspond to the conditions simulated for the 2017 data-taking period. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Signal acceptance times efficiency ($A\times\epsilon$) for each of the generated chargino masses and lifetimes for $\mathrm{p}\mathrm{p} \rightarrow \widetilde{\chi}^\pm_{1} \widetilde{\chi}^0_{1,2}$ events, in the case of a purely higgsino neutralino LSP. The denominator for the acceptance is the total number of $\widetilde{\chi}^\pm_{1} \widetilde{\chi}^0_{1,2}$ events generated, while the numerator is the number of those events that are selected by the signal selection after being processed with the same reconstruction software used on the data. These $A\times\epsilon$ values correspond to the conditions simulated for the 2017 data-taking period. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Signal acceptance times efficiency ($A\times\epsilon$) for each of the generated chargino masses and lifetimes for $\mathrm{p}\mathrm{p} \rightarrow \widetilde{\chi}^\pm_{1} \widetilde{\chi}^\mp_{1}$ events, in the case of a purely wino neutralino LSP. The denominator for the acceptance is the total number of $\widetilde{\chi}^\pm_{1} \widetilde{\chi}^\mp_{1}$ events generated, while the numerator is the number of those events that are selected by the signal selection after being processed with the same reconstruction software used on the data. These $A\times\epsilon$ values correspond to the conditions simulated for the 2018A data-taking period. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Signal acceptance times efficiency ($A\times\epsilon$) for each of the generated chargino masses and lifetimes for $\mathrm{p}\mathrm{p} \rightarrow \widetilde{\chi}^\pm_{1} \widetilde{\chi}^\mp_{1}$ events, in the case of a purely wino neutralino LSP. The denominator for the acceptance is the total number of $\widetilde{\chi}^\pm_{1} \widetilde{\chi}^\mp_{1}$ events generated, while the numerator is the number of those events that are selected by the signal selection after being processed with the same reconstruction software used on the data. These $A\times\epsilon$ values correspond to the conditions simulated for the 2018A data-taking period. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Signal acceptance times efficiency ($A\times\epsilon$) for each of the generated chargino masses and lifetimes for $\mathrm{p}\mathrm{p} \rightarrow \widetilde{\chi}^\pm_{1} \widetilde{\chi}^0_{1}$ events, in the case of a purely wino neutralino LSP. The denominator for the acceptance is the total number of $\widetilde{\chi}^\pm_{1} \widetilde{\chi}^0_{1}$ events generated, while the numerator is the number of those events that are selected by the signal selection after being processed with the same reconstruction software used on the data. These $A\times\epsilon$ values correspond to the conditions simulated for the 2018A data-taking period. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Signal acceptance times efficiency ($A\times\epsilon$) for each of the generated chargino masses and lifetimes for $\mathrm{p}\mathrm{p} \rightarrow \widetilde{\chi}^\pm_{1} \widetilde{\chi}^0_{1}$ events, in the case of a purely wino neutralino LSP. The denominator for the acceptance is the total number of $\widetilde{\chi}^\pm_{1} \widetilde{\chi}^0_{1}$ events generated, while the numerator is the number of those events that are selected by the signal selection after being processed with the same reconstruction software used on the data. These $A\times\epsilon$ values correspond to the conditions simulated for the 2018A data-taking period. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Signal acceptance times efficiency ($A\times\epsilon$) for each of the generated chargino masses and lifetimes for $\mathrm{p}\mathrm{p} \rightarrow \widetilde{\chi}^\pm_{1} \widetilde{\chi}^\mp_{1}$ events, in the case of a purely higgsino neutralino LSP. The denominator for the acceptance is the total number of $\widetilde{\chi}^\pm_{1} \widetilde{\chi}^\mp_{1}$ events generated, while the numerator is the number of those events that are selected by the signal selection after being processed with the same reconstruction software used on the data. These $A\times\epsilon$ values correspond to the conditions simulated for the 2018A data-taking period. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Signal acceptance times efficiency ($A\times\epsilon$) for each of the generated chargino masses and lifetimes for $\mathrm{p}\mathrm{p} \rightarrow \widetilde{\chi}^\pm_{1} \widetilde{\chi}^\mp_{1}$ events, in the case of a purely higgsino neutralino LSP. The denominator for the acceptance is the total number of $\widetilde{\chi}^\pm_{1} \widetilde{\chi}^\mp_{1}$ events generated, while the numerator is the number of those events that are selected by the signal selection after being processed with the same reconstruction software used on the data. These $A\times\epsilon$ values correspond to the conditions simulated for the 2018A data-taking period. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Signal acceptance times efficiency ($A\times\epsilon$) for each of the generated chargino masses and lifetimes for $\mathrm{p}\mathrm{p} \rightarrow \widetilde{\chi}^\pm_{1} \widetilde{\chi}^0_{1,2}$ events, in the case of a purely higgsino neutralino LSP. The denominator for the acceptance is the total number of $\widetilde{\chi}^\pm_{1} \widetilde{\chi}^0_{1,2}$ events generated, while the numerator is the number of those events that are selected by the signal selection after being processed with the same reconstruction software used on the data. These $A\times\epsilon$ values correspond to the conditions simulated for the 2018A data-taking period. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Signal acceptance times efficiency ($A\times\epsilon$) for each of the generated chargino masses and lifetimes for $\mathrm{p}\mathrm{p} \rightarrow \widetilde{\chi}^\pm_{1} \widetilde{\chi}^0_{1,2}$ events, in the case of a purely higgsino neutralino LSP. The denominator for the acceptance is the total number of $\widetilde{\chi}^\pm_{1} \widetilde{\chi}^0_{1,2}$ events generated, while the numerator is the number of those events that are selected by the signal selection after being processed with the same reconstruction software used on the data. These $A\times\epsilon$ values correspond to the conditions simulated for the 2018A data-taking period. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Signal acceptance times efficiency ($A\times\epsilon$) for each of the generated chargino masses and lifetimes for $\mathrm{p}\mathrm{p} \rightarrow \widetilde{\chi}^\pm_{1} \widetilde{\chi}^\mp_{1}$ events, in the case of a purely wino neutralino LSP. The denominator for the acceptance is the total number of $\widetilde{\chi}^\pm_{1} \widetilde{\chi}^\mp_{1}$ events generated, while the numerator is the number of those events that are selected by the signal selection after being processed with the same reconstruction software used on the data. These $A\times\epsilon$ values correspond to the conditions simulated for the 2018B data-taking period. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Signal acceptance times efficiency ($A\times\epsilon$) for each of the generated chargino masses and lifetimes for $\mathrm{p}\mathrm{p} \rightarrow \widetilde{\chi}^\pm_{1} \widetilde{\chi}^\mp_{1}$ events, in the case of a purely wino neutralino LSP. The denominator for the acceptance is the total number of $\widetilde{\chi}^\pm_{1} \widetilde{\chi}^\mp_{1}$ events generated, while the numerator is the number of those events that are selected by the signal selection after being processed with the same reconstruction software used on the data. These $A\times\epsilon$ values correspond to the conditions simulated for the 2018B data-taking period. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Signal acceptance times efficiency ($A\times\epsilon$) for each of the generated chargino masses and lifetimes for $\mathrm{p}\mathrm{p} \rightarrow \widetilde{\chi}^\pm_{1} \widetilde{\chi}^0_{1}$ events, in the case of a purely wino neutralino LSP. The denominator for the acceptance is the total number of $\widetilde{\chi}^\pm_{1} \widetilde{\chi}^0_{1}$ events generated, while the numerator is the number of those events that are selected by the signal selection after being processed with the same reconstruction software used on the data. These $A\times\epsilon$ values correspond to the conditions simulated for the 2018B data-taking period. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Signal acceptance times efficiency ($A\times\epsilon$) for each of the generated chargino masses and lifetimes for $\mathrm{p}\mathrm{p} \rightarrow \widetilde{\chi}^\pm_{1} \widetilde{\chi}^0_{1}$ events, in the case of a purely wino neutralino LSP. The denominator for the acceptance is the total number of $\widetilde{\chi}^\pm_{1} \widetilde{\chi}^0_{1}$ events generated, while the numerator is the number of those events that are selected by the signal selection after being processed with the same reconstruction software used on the data. These $A\times\epsilon$ values correspond to the conditions simulated for the 2018B data-taking period. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Signal acceptance times efficiency ($A\times\epsilon$) for each of the generated chargino masses and lifetimes for $\mathrm{p}\mathrm{p} \rightarrow \widetilde{\chi}^\pm_{1} \widetilde{\chi}^\mp_{1}$ events, in the case of a purely higgsino neutralino LSP. The denominator for the acceptance is the total number of $\widetilde{\chi}^\pm_{1} \widetilde{\chi}^\mp_{1}$ events generated, while the numerator is the number of those events that are selected by the signal selection after being processed with the same reconstruction software used on the data. These $A\times\epsilon$ values correspond to the conditions simulated for the 2018B data-taking period. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Signal acceptance times efficiency ($A\times\epsilon$) for each of the generated chargino masses and lifetimes for $\mathrm{p}\mathrm{p} \rightarrow \widetilde{\chi}^\pm_{1} \widetilde{\chi}^\mp_{1}$ events, in the case of a purely higgsino neutralino LSP. The denominator for the acceptance is the total number of $\widetilde{\chi}^\pm_{1} \widetilde{\chi}^\mp_{1}$ events generated, while the numerator is the number of those events that are selected by the signal selection after being processed with the same reconstruction software used on the data. These $A\times\epsilon$ values correspond to the conditions simulated for the 2018B data-taking period. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Signal acceptance times efficiency ($A\times\epsilon$) for each of the generated chargino masses and lifetimes for $\mathrm{p}\mathrm{p} \rightarrow \widetilde{\chi}^\pm_{1} \widetilde{\chi}^0_{1,2}$ events, in the case of a purely higgsino neutralino LSP. The denominator for the acceptance is the total number of $\widetilde{\chi}^\pm_{1} \widetilde{\chi}^0_{1,2}$ events generated, while the numerator is the number of those events that are selected by the signal selection after being processed with the same reconstruction software used on the data. These $A\times\epsilon$ values correspond to the conditions simulated for the 2018B data-taking period. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Signal acceptance times efficiency ($A\times\epsilon$) for each of the generated chargino masses and lifetimes for $\mathrm{p}\mathrm{p} \rightarrow \widetilde{\chi}^\pm_{1} \widetilde{\chi}^0_{1,2}$ events, in the case of a purely higgsino neutralino LSP. The denominator for the acceptance is the total number of $\widetilde{\chi}^\pm_{1} \widetilde{\chi}^0_{1,2}$ events generated, while the numerator is the number of those events that are selected by the signal selection after being processed with the same reconstruction software used on the data. These $A\times\epsilon$ values correspond to the conditions simulated for the 2018B data-taking period. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Summary of the estimated backgrounds and the observation. The first and second uncertainties shown are the statistical and systematic contributions, respectively.

Summary of the estimated backgrounds and the observation. The first and second uncertainties shown are the statistical and systematic contributions, respectively.

The standard deviation of the jet charge distributions with different track $p_{T}$ thresholds and $\kappa$ value pf 0.7 for pp collisions and in the various event centrality bins for PbPb collisions compared with the PYTHIA6 prediction.

Fitting results for the extraction of gluon-like jet fractions in pp and PbPb data shown for different track $p_{T}$ threshold values and $p_{T}$-weighting factor $\kappa$ values of 0.5.

Fitting results for the extraction of gluon-like jet fractions in pp and PbPb data shown for $p_{T}$-weighting factor $\kappa$ values of 0.3, 0.5, and 0.7 and minimum track $p_{T}$ of 1 GeV.

Fitting results for the extraction of gluon-like jet fractions in pp and PbPb data shown for $p_{T}$-weighting factor $\kappa$ values of 0.3, 0.5, and 0.7 and minimum track $p_{T}$ of 2 GeV.

Unfolded jet charge measurements for the $p_{T}$-weighting factor $\kappa = 0.5$ and a minimum track $p_{T}$ of 2 GeV for inclusive jets in pp and PbPb data. The PbPb results are shown for different centrality regions.

Unfolded jet charge measurements for the $p_{T}$-weighting factor $\kappa = 0.5$ and a minimum track $p_{T}$ of 4 GeV for inclusive jets in pp and PbPb data. The PbPb results are shown for different centrality regions.

Unfolded jet charge measurements for the $p_{T}$-weighting factor $\kappa = 0.5$ and a minimum track $p_{T}$ of 5 GeV for inclusive jets in pp and PbPb data. The PbPb results are shown for different centrality regions.

Unfolded jet charge measurements for a minimum track $p_{T}$ threshold of 1 GeV and $p_{T}$-weighting factor $\kappa = 0.3$ for inclusive jets in pp and PbPb data. The PbPb results are shown for different centrality regions.

Unfolded jet charge measurements for a minimum track $p_{T}$ threshold of 1 GeV and $p_{T}$-weighting factor $\kappa = 0.7$ for inclusive jets in pp and PbPb data. The PbPb results are shown for different centrality regions.

Unfolded jet charge measurements for a minimum track $p_{T}$ threshold of 2 GeV and $p_{T}$-weighting factor $\kappa = 0.3$ for inclusive jets in pp and PbPb data. The PbPb results are shown for different centrality regions.

Unfolded jet charge measurements for a minimum track $p_{T}$ threshold of 2 GeV and $p_{T}$-weighting factor $\kappa = 0.7$ for inclusive jets in pp and PbPb data. The PbPb results are shown for different centrality regions.

Nuclear modification factors $R_{AA}$ as a function of $E_{T}^{\gamma}$ measured in the 0–100% centrality ranges in PbPb.

constraint on CP-odd contribution at 68% CL

exclusion significance on pure CP odd contribution

Differential cross section as a function of the transverse momentum of the pion pair at 13 TeV, compared with generator-level simulations.

Differential cross section as a function of the rapidity of the pion pair at 5.02 TeV, compared with generator-level simulations.

Differential cross section as a function of the rapidity of the pion pair at 13 TeV, compared with generator-level simulations.