Data vs. the ABCD method background prediction for 2017 in $\mathrm{SR_{b}^{mm}}$. Events are divided by the bin width, hence fractional data counts. Error bars show statistical uncertainties of data. The blue band shows the propagated uncertainty of all individual fit variations in a given bin, which we consider to be uncorrelated. The lower panels show the ratio of the observed data to the background estimation.

Data vs. the ABCD method background prediction for 2018 in $\mathrm{SR_{b}^{mm}}$. Events are divided by the bin width, hence fractional data counts. Error bars show statistical uncertainties of data. The blue band shows the propagated uncertainty of all individual fit variations in a given bin, which we consider to be uncorrelated. The lower panels show the ratio of the observed data to the background estimation.

Data vs. the ABCD method background prediction for 2016 in $\mathrm{SR_{b+\textrm{j}/b}^{mm}}$. Events are divided by the bin width, hence fractional data counts. Error bars show statistical uncertainties of data. The blue band shows the propagated uncertainty of all individual fit variations in a given bin, which we consider to be uncorrelated. The lower panels show the ratio of the observed data to the background estimation.

Data vs. the ABCD method background prediction for 2017 in $\mathrm{SR_{b+\textrm{j}/b}^{mm}}$. Events are divided by the bin width, hence fractional data counts. Error bars show statistical uncertainties of data. The blue band shows the propagated uncertainty of all individual fit variations in a given bin, which we consider to be uncorrelated. The lower panels show the ratio of the observed data to the background estimation.

Data vs. the ABCD method background prediction for 2018 in $\mathrm{SR_{b+\textrm{j}/b}^{mm}}$. Events are divided by the bin width, hence fractional data counts. Error bars show statistical uncertainties of data. The blue band shows the propagated uncertainty of all individual fit variations in a given bin, which we consider to be uncorrelated. The lower panels show the ratio of the observed data to the background estimation.

The asymptotic 95% CL limits on the product of cross section ($\sigma$), branching fraction into a pair of muons ($\mathcal{B}$) to dimuons, acceptance (A), and efficiency ($\epsilon$) in $\mathrm{SR_{b}^{mm}}$. A combination of both limits depends on the relative acceptance contributions in each region and is omitted here.

The asymptotic 95% CL limits on the product of cross section ($\sigma$), branching fraction into a pair of muons ($\mathcal{B}$) to dimuons, acceptance (A), and efficiency ($\epsilon$) in $\mathrm{SR_{b+\textrm{j}/b}^{mm}}$. A combination of both limits depends on the relative acceptance contributions in each region and is omitted here.

Cutflow for signal samples in 2016. Samples are divided by generated mass, signal region, and the b to s quark flavor changing coupling of the $Z^\prime$, dbs. For some mass values, multiple values of this coupling strength have been generated. It is described in this minimal lagrangian: $\mathcal{L} \supset Z^{\prime}_{\eta} \Big[ g_{\mu}\, \bar{\mu}\, \gamma^{\eta}\, \mu + \big( g_b\, \delta_{bs}\, \bar{s}\, \gamma^{\eta}\, P_{L}\, b + \text{h.c.} \big) \Big]$. The cutflow shows the selection into signal regions, and then the effects of specialized HTLT and RelMET selections, which grow with greater mass.

Cutflow for signal samples in 2017. Samples are divided by generated mass, signal region, and the b to s quark flavor changing coupling of the $Z^\prime$, dbs. For some mass values, multiple values of this coupling strength have been generated. It is described in this minimal lagrangian: $\mathcal{L} \supset Z^{\prime}_{\eta} \Big[ g_{\mu}\, \bar{\mu}\, \gamma^{\eta}\, \mu + \big( g_b\, \delta_{bs}\, \bar{s}\, \gamma^{\eta}\, P_{L}\, b + \text{h.c.} \big) \Big]$. The cutflow shows the selection into signal regions, and then the effects of specialized HTLT and RelMET selections, which grow with greater mass.

Cutflow for signal samples in 2018. Samples are divided by generated mass, signal region, and the b to s quark flavor changing coupling of the $Z^\prime$, dbs. For some mass values, multiple values of this coupling strength have been generated. It is described in this minimal lagrangian: $\mathcal{L} \supset Z^{\prime}_{\eta} \Big[ g_{\mu}\, \bar{\mu}\, \gamma^{\eta}\, \mu + \big( g_b\, \delta_{bs}\, \bar{s}\, \gamma^{\eta}\, P_{L}\, b + \text{h.c.} \big) \Big]$. The cutflow shows the selection into signal regions, and then the effects of specialized HTLT and RelMET selections, which grow with greater 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 trailing lepton $p_T$.

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 |$\eta$| < 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.

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.

Expected and observed exclusion limits at the 95\% CL as a function of $m(\mathrm{H}^{\pm})$ for $\sigma_\mathrm{VBF}(\mathrm{H}^{\pm}) \, \mathcal{B}(\mathrm{H}^{\pm} \rightarrow \mathrm{W}^{\pm}\mathrm{Z})$ in the $\mathrm{ZV}$ final state.

Expected and observed exclusion limits at the 95\% CL as a function of $m(\mathrm{H}^{\pm\pm})$ for $\sigma_\mathrm{VBF}(\mathrm{H}^{\pm\pm}) \, \mathcal{B}(\mathrm{H}^{\pm\pm} \rightarrow \mathrm{W}^{\pm}\mathrm{W}^{\pm})$ in the $\mathrm{WV}$ final state.

Expected and observed exclusion limits at the 95\% CL for $s_{\mathrm{H}}$ in the Georgi-Machacek model.

$\mathrm{m_{\mathrm{WV}}}$ distribution in the $\mathrm{WV}$ channel. The predicted yields are shown with their best-fit normalizations from the background-only fit.

$\mathrm{m_{\mathrm{ZV}}}$ distribution in the $\mathrm{ZV}$ channel. The predicted yields are shown with their best-fit normalizations from the background-only fit.

Covariance matrix for all the $\mathrm{m_{\mathrm{WV}}}$ bins used in the $\mathrm{WV}$ channel. The mass distributions are binned as follows: $\mathrm{m_{\mathrm{WV}}}$ = [600, 700, 800, 900, 1000, 1200, 1500, 2000, $\infty$] GeV. The covariance matrix from the background-only fit is shown.

Covariance matrix for all the $\mathrm{m_{\mathrm{ZV}}}$ bins used in the $\mathrm{ZV}$ channel. The mass distributions are binned as follows: $\mathrm{m_{\mathrm{ZV}}}$ = [600, 700, 800, 900, 1000, 1200, 1500, 2000, $\infty$] GeV. The covariance matrix from the background-only fit is shown.