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

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

Distributions of BDT score in the WZ signal region.

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

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

Absolute 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.

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

Absolute 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 $m_{T}^{WZ}$ 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 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.

Observed and expected multivariate discriminant distribution in the $\ell\ell\ell\ell jj$ SR.

Observed and expected multivariate discriminant distribution in the $\ell\ell\nu\nu jj$ SR.

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 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 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 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 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 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 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 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 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 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 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 $\mathrm{p}\mathrm{p} \rightarrow \widetilde{\chi}^\pm_{1} \widetilde{\chi}^0_{1}$ 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 $\mathrm{p}\mathrm{p} \rightarrow \widetilde{\chi}^\pm_{1} \widetilde{\chi}^0_{1,2}$ 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 $\mathrm{p}\mathrm{p} \rightarrow \widetilde{\chi}^\pm_{1} \widetilde{\chi}^0_{1}$ 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 $\mathrm{p}\mathrm{p} \rightarrow \widetilde{\chi}^\pm_{1} \widetilde{\chi}^0_{1,2}$ 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 $\mathrm{p}\mathrm{p} \rightarrow \widetilde{\chi}^\pm_{1} \widetilde{\chi}^0_{1}$ 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 $\mathrm{p}\mathrm{p} \rightarrow \widetilde{\chi}^\pm_{1} \widetilde{\chi}^0_{1,2}$ 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.

Correlation matrix between the fiducial cross sections for the four individual decay final states and the $ZZ^{*}$ normalisation factor.

Differential fiducial cross section for the transverse momentum $p_{T}^{4l}$ of the Higgs boson. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 . Measured value in the last bin is un upper limit at 95% CL.

Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the transverse momentum $p_{T}^{4l}$ of the Higgs boson.

Differential fiducial cross section for the invariant mass $m_{12}$ of the leading Z boson. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .

Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the invariant mass $m_{12}$ of the leading Z boson.

Differential fiducial cross section for the invariant mass $m_{34}$ of the subleading Z boson. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .

Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the invariant mass $m_{34}$ of the subleading Z boson.

Differential fiducial cross section for the rapidity $|y_{4l}|$ of the Higgs boson. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .

Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the rapidity $|y_{4l}|$ of the Higgs boson.

Differential fiducial cross section for the production angle $|\cos\theta^{*}|$ of the leading Z boson. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .

Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the production angle $|\cos\theta^{*}|$ of the leading Z boson.

Differential fiducial cross section for the production angle $\cos\theta_{1}$ of the anti-lepton from the leading Z boson. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .

Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the production angle $\cos\theta_{1}$ of the anti-lepton from the leading Z boson.

Differential fiducial cross section for the production angle $\cos\theta_{2}$ of the anti-lepton from the subleading Z boson. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .

Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the production angle $\cos\theta_{2}$ of the anti-lepton from the subleading Z boson.

Differential fiducial cross section for the azimuthal angle $\phi$ of the decay planes of the two reconstructed Z bosons. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .

Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the azimuthal angle $\phi$ of the decay planes of the two reconstructed Z bosons.

Differential fiducial cross section for the azimuthal angle $\phi_{1}$ of the decay plane of the leading Z boson and the plane formed between its four-momentum and the z-axis. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .

Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the azimuthal angle $\phi_{1}$ of the decay plane of the leading Z boson and the plane formed between its four-momentum and the z-axis.

Differential fiducial cross section for the jet multiplicity $N_{jets}$. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .

Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the jet multiplicity $N_{jets}$.

Differential fiducial cross section for the inclusive jet multiplicity $N_{jets}$. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .

Differential fiducial cross section for the number of b-quark initiated jets $N_{b-jets}$. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .

Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the number of b-quark initiated jets $N_{b-jets}$.

Differential fiducial cross section for the transverse momentum of the leading jet $p_{T}^{lead.jet}$ in events with at least one jet. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .

Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the transverse momentum of the leading jet $p_{T}^{lead.jet}$ in events with at least one jet.

Differential fiducial cross section for the transverse momentum of the subleading jet $p_{T}^{sublead.jet}$ in events with at least two jets. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .

Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the transverse momentum of the subleading jet $p_{T}^{sublead.jet}$ in events with at least two jets.

Differential fiducial cross section for the invariant mass of the two highest-pT jets $m_{jj}$ in events with at least two jets. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .

Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the invariant mass of the two highest-pT jets $m_{jj}$ in events with at least two jets.

Differential fiducial cross section for the distance between the two highest-pT jets in pseudorapidity $\Delta\eta_{jj}$. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .

Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the distance between the two highest-pT jets in pseudorapidity $\Delta\eta_{jj}$.

Differential fiducial cross section for the distance between the two highest-pT jets in $\phi$ $\Delta\phi_{jj}$. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .

Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the distance between the two highest-pT jets in $\phi$ $\Delta\phi_{jj}$.

Differential fiducial cross section for the transverse momentum of the four lepton plus jet system, in events with at least one jet $p_{T}^{4lj}$. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .

Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the transverse momentum of the four lepton plus jet system, in events with at least one jet $p_{T}^{4lj}$.

Differential fiducial cross section for the transverse momentum of the four lepton plus di-jet system, in events with at least two jets $p_{T}^{4ljj}$. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 . Measured value in the last bin is un upper limit at 95% CL.

Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the transverse momentum of the four lepton plus di-jet system, in events with at least two jets $p_{T}^{4ljj}$.

Differential fiducial cross section for the invariant mass of the four lepton plus jet system in events with at least one jet $m_{4lj}$. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .

Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the invariant mass of the four lepton plus jet system in events with at least one jet $m_{4lj}$.

Differential fiducial cross section for the invariant mass of the four lepton plus di-jet system in events with at least two jets $m_{4ljj}$. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .

Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the invariant mass of the four lepton plus di-jet system in events with at least two jets $m_{4ljj}$.

Differential fiducial cross section for the leading vs. subleading Z boson mass $m_{12}$vs.$m_{34}$. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .

Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the leading vs. subleading Z boson mass $m_{12}$vs.$m_{34}$.

Differential fiducial cross section for the leading vs. subleading Z boson mass $m_{12}$vs.$m_{34}$ in $ll\mu\mu$ final states. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .

Differential fiducial cross section for the leading vs. subleading Z boson mass $m_{12}$vs.$m_{34}$ in $llee$ final states. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .

Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the leading vs. subleading Z boson mass m12 vs. m34 in $ll\mu\mu$ and $llee$ final states.

Differential fiducial cross section of the $p_{T}^{4l}$ distribution in $|y_{4l}|$ bins. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .

Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section of the $p_{T}^{4l}$ distribution in $|y_{4l}|$ bins.

Differential fiducial cross section of the $p_{T}^{4l}$ distribution in $N_{jets}$ bins. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .

Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section of the $p_{T}^{4l}$ distribution in $N_{jets}$ bins.

Differential fiducial cross section for transverse momentum of the four lepton system vs. the transverse momentum of the four lepton plus jet system $p_{T}^{4l}$vs.$p_{T}^{4lj}$. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .

Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for transverse momentum of the four lepton system vs. the transverse momentum of the four lepton plus jet system $p_{T}^{4l}$vs.$p_{T}^{4lj}$.

Differential fiducial cross section for the transverse momentum of the four lepton plus jet system vs the invariant mass of the four lepton plus jet system $p_{T}^{4l}$vs.$m_{4lj}$. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .

Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the transverse momentum of the four lepton plus jet system vs the invariant mass of the four lepton plus jet system $p_{T}^{4l}$vs.$m_{4lj}$.

Differential fiducial cross section for the transverse momentum of the four lepton vs the transverse momentum of the leading jet $p_{T}^{4l}$vs.$p_{T}^{l.jet}$. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .

Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the transverse momentum of the four lepton vs the transverse momentum of the leading jet $p_{T}^{4l}$vs.$p_{T}^{lead.jet}$.

Differential fiducial cross section for the transverse momentum of the leading jet vs the rapidity of the leading jet $p_{T}^{lead.jet}$vs.$|y^{lead.jet}|$. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .

Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the transverse momentum of the leading jet vs the rapidity of the leading jet $p_{T}^{lead.jet}$vs.$|y^{lead.jet}|$.

Differential fiducial cross section for the transverse momentum of the leading jet vs the transverse momentum of the subleading jet $p_{T}^{lead.jet}$vs.$p_{T}^{sublead.jet}$. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .

Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the transverse momentum of the leading jet vs the transverse momentum of the subleading jet $p_{T}^{lead.jet}$vs.$p_{T}^{sublead.jet}$.

Differential fiducial cross section for the leading Z boson mass $m_{12}$ in $4\mu$ and $4e$ final states. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .

Differential fiducial cross section for the leading Z boson mass $m_{12}$ in $2e2\mu$ and $2\mu2e$ final states. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .

Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the leading Z boson mass $m_{12}$ in $4l$ and $2l2l$ final states.

Differential fiducial cross section for the subleading Z boson mass $m_{34}$ in $4\mu$ and $4e$ final states. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .

Differential fiducial cross section for the subleading Z boson mass $m_{34}$ in $2e2\mu$ and $2\mu2e$ final states. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .

Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the subleading Z boson mass $m_{34}$ in $4l$ and $2l2l$ final states.

Differential fiducial cross section for the azimuthal angle $\phi$ of the decay planes of the two reconstructed Z bosons in $4\mu$ and $4e$ final states. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .

Differential fiducial cross section for the azimuthal angle $\phi$ of the decay planes of the two reconstructed Z bosons in $2e2\mu$ and $2\mu2e$ final states. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .

Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the azimuthal angle $\phi$ of the decay planes of the two reconstructed Z bosons in $4l$ and $2l2l$ final states.

Differential fiducial cross section for the leading vs. subleading Z boson mass $m_{12}$vs.$m_{34}$ in $4\mu$ and $4e$ final states. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .

Differential fiducial cross section for the leading vs. subleading Z boson mass $m_{12}$vs.$m_{34}$ in $2\mu2e$ and $2e2\mu$ final states. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .

Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the leading vs. subleading Z boson mass $m_{12}$vs.$m_{34}$ in $4l$ and $2l2l$ final states.

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