Observed 95% CL exclusion limits on the simplified models of chargino-pair production decaying via W bosons.

$+1\sigma$ observed 95% CL exclusion limits on the simplified models of chargino-pair production decaying via W bosons.

$-1\sigma$ observed 95% CL exclusion limits on the simplified models of chargino-pair production decaying via W bosons.

Expected 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and Z bosons.

$+1\sigma$ expected 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and Z bosons.

$-1\sigma$ expected 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and Z bosons.

Observed 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and Z bosons.

$+1\sigma$ observed 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and Z bosons.

$-1\sigma$ observed 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and Z bosons.

Expected 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and h bosons.

$+1\sigma$ expected 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and h bosons.

$-1\sigma$ expected 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and h bosons.

Observed 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and h bosons.

$+1\sigma$ observed 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and h bosons.

$-1\sigma$ observed 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and h bosons.

Expected 95% CL exclusion limits on the simplified models of higgsino GGM scenarios.

$+1\sigma$ expected 95% CL exclusion limits on the simplified models of higgsino GGM scenarios.

$-1\sigma$ expected 95% CL exclusion limits on the simplified models of higgsino GGM scenarios.

Observed 95% CL exclusion limits on the simplified models of higgsino GGM scenarios.

$+1\sigma$ observed 95% CL exclusion limits on the simplified models of higgsino GGM scenarios.

$-1\sigma$ observed 95% CL exclusion limits on the simplified models of higgsino GGM scenarios.

Observed upper limit on the signal cross section in fb for the production of $\tilde{\chi}_1^{+}\tilde{\chi}_{1}^{-}$.

The analyses used in combination for each scenario to set limits in models of the production of $\tilde{\chi}_1^{+}\tilde{\chi}_{1}^{-}$.

Observed upper limit on the signal cross section in fb for chargino--neutralino production decaying via W and Z bosons.

The analyses used in combination for each scenario to set limits in models of chargino--neutralino production decaying via W and Z bosons.

Expected 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and Z bosons.

$+1\sigma$ expected 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and Z bosons.

$-1\sigma$ expected 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and Z bosons.

Observed 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and Z bosons.

$+1\sigma$ observed 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and Z bosons.

$-1\sigma$ observed 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and Z bosons.

Observed upper limit on the signal cross section in fb for chargino--neutralino production decaying via W and h bosons.

The analyses used in combination for each scenario to set limits in models of chargino--neutralino production decaying via W and h bosons.

Observed upper limit on the signal cross section in fb for higgsino GGM scenarios.

The analyses used in combination for each scenario to set limits in higgsino GGM scenarios.

Expected (dashed black line) and observed (solid red line) 95% CL exclusion limits on the higgsino simplified model being considered. These are shown with $\pm 1\sigma_{\mathrm{exp}}$ (yellow band) from experimental systematic and statistical uncertainties, and with $\pm 1\sigma_{\mathrm{theory}}^{\mathrm{SUSY}}$ (red dotted lines) from signal cross-section uncertainties, respectively. The limits set by the latest ATLAS searches using the soft lepton and disappearing track signatures are illustrated by the blue and green regions, respectively, while the limit imposed by the LEP experiments is shown in gray. The dot-dashed gray line indicates the predicted mass-splitting for the pure higgsino scenario.

Expected (dashed black line) and observed (solid red line) 95% CL exclusion limits on the higgsino simplified model being considered. These are shown with $\pm 1\sigma_{\mathrm{exp}}$ (yellow band) from experimental systematic and statistical uncertainties, and with $\pm 1\sigma_{\mathrm{theory}}^{\mathrm{SUSY}}$ (red dotted lines) from signal cross-section uncertainties, respectively. The limits set by the latest ATLAS searches using the soft lepton and disappearing track signatures are illustrated by the blue and green regions, respectively, while the limit imposed by the LEP experiments is shown in gray. The dot-dashed gray line indicates the predicted mass-splitting for the pure higgsino scenario.

Expected (dashed black line) and observed (solid red line) 95% CL exclusion limits on the higgsino simplified model being considered. These are shown with $\pm 1\sigma_{\mathrm{exp}}$ (yellow band) from experimental systematic and statistical uncertainties, and with $\pm 1\sigma_{\mathrm{theory}}^{\mathrm{SUSY}}$ (red dotted lines) from signal cross-section uncertainties, respectively. The limits set by the latest ATLAS searches using the soft lepton and disappearing track signatures are illustrated by the blue and green regions, respectively, while the limit imposed by the LEP experiments is shown in gray. The dot-dashed gray line indicates the predicted mass-splitting for the pure higgsino scenario.

Expected (dashed black line) and observed (solid red line) 95% CL exclusion limits on the higgsino simplified model being considered. These are shown with $\pm 1\sigma_{\mathrm{exp}}$ (yellow band) from experimental systematic and statistical uncertainties, and with $\pm 1\sigma_{\mathrm{theory}}^{\mathrm{SUSY}}$ (red dotted lines) from signal cross-section uncertainties, respectively. The limits set by the latest ATLAS searches using the soft lepton and disappearing track signatures are illustrated by the blue and green regions, respectively, while the limit imposed by the LEP experiments is shown in gray. The dot-dashed gray line indicates the predicted mass-splitting for the pure higgsino scenario.

Expected and observed CLs values per signal point represented by the grey numbers. The expected (dashed) and observed (solid) 95% CL exclusion limits are overlaid along with $\pm 1\sigma_{\mathrm{exp}}$ (yellow band) from experimental systematic and statistical uncertainties, and with $\pm 1\sigma_{\mathrm{theory}}^{\mathrm{SUSY}}$ (red dotted lines) from signal cross-section uncertainties, respectively.

Expected and observed CLs values per signal point represented by the grey numbers. The expected (dashed) and observed (solid) 95% CL exclusion limits are overlaid along with $\pm 1\sigma_{\mathrm{exp}}$ (yellow band) from experimental systematic and statistical uncertainties, and with $\pm 1\sigma_{\mathrm{theory}}^{\mathrm{SUSY}}$ (red dotted lines) from signal cross-section uncertainties, respectively.

Expected and observed cross-section upper-limit per signal point represented by the grey numbers. The expected (dashed) and observed (solid) 95% CL exclusion limits are overlaid along with $\pm 1\sigma_{\mathrm{exp}}$ (yellow band) from experimental systematic and statistical uncertainties, and with $\pm 1\sigma_{\mathrm{theory}}^{\mathrm{SUSY}}$ (red dotted lines) from signal cross-section uncertainties, respectively.

Expected and observed cross-section upper-limit per signal point represented by the grey numbers. The expected (dashed) and observed (solid) 95% CL exclusion limits are overlaid along with $\pm 1\sigma_{\mathrm{exp}}$ (yellow band) from experimental systematic and statistical uncertainties, and with $\pm 1\sigma_{\mathrm{theory}}^{\mathrm{SUSY}}$ (red dotted lines) from signal cross-section uncertainties, respectively.

Truth-level signal acceptances for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$) in a SR with the $S(d_0)$ requirement removed. The acceptance is defined as the fraction of accepted events divided by the total number of events in the generator-level signal Monte Carlo simulation, where the signal candidate track is identified as the charged particle with the largest distance between the interaction vertex and the secondary vertex of the higgsino decays.

Truth-level signal acceptances for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$) in a SR with the $S(d_0)$ requirement removed. The acceptance is defined as the fraction of accepted events divided by the total number of events in the generator-level signal Monte Carlo simulation, where the signal candidate track is identified as the charged particle with the largest distance between the interaction vertex and the secondary vertex of the higgsino decays.

Truth-level signal acceptances for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$) in a SR with the $S(d_0)$ requirement removed. The acceptance is defined as the fraction of accepted events divided by the total number of events in the generator-level signal Monte Carlo simulation, where the signal candidate track is identified as the charged particle with the largest distance between the interaction vertex and the secondary vertex of the higgsino decays.

Truth-level signal acceptances for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$) in a SR with the $S(d_0)$ requirement removed. The acceptance is defined as the fraction of accepted events divided by the total number of events in the generator-level signal Monte Carlo simulation, where the signal candidate track is identified as the charged particle with the largest distance between the interaction vertex and the secondary vertex of the higgsino decays.

Truth-level signal acceptances for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$) in a SR with the $S(d_0)$ requirement removed. The acceptance is defined as the fraction of accepted events divided by the total number of events in the generator-level signal Monte Carlo simulation, where the signal candidate track is identified as the charged particle with the largest distance between the interaction vertex and the secondary vertex of the higgsino decays.

Truth-level signal acceptances for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$) in a SR with the $S(d_0)$ requirement removed. The acceptance is defined as the fraction of accepted events divided by the total number of events in the generator-level signal Monte Carlo simulation, where the signal candidate track is identified as the charged particle with the largest distance between the interaction vertex and the secondary vertex of the higgsino decays.

Signal efficiencies in SR-Low for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.

Signal efficiencies in SR-Low for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.

Signal efficiencies in SR-Low for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.

Signal efficiencies in SR-Low for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.

Signal efficiencies in SR-Low for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.

Signal efficiencies in SR-Low for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.

Signal efficiencies in SR-High for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.

Signal efficiencies in SR-High for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.

Signal efficiencies in SR-High for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.

Signal efficiencies in SR-High for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.

Signal efficiencies in SR-High for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.

Signal efficiencies in SR-High for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.

Event selection cutflows for signal samples with $m(\tilde{\chi}_{1}^0)$ = 150 GeV and $\Delta m(\tilde{\chi}_{1}^\pm, \tilde{\chi}_{1}^0)$ = 1.5, 1.0, and 0.75 GeV, including all six production processes ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$). The cross-section used to obtain the initial number of events ($\sigma(\mathrm{n}_{\mathrm{jets}}) \geq 1$) refers to an emission of at least one gluon or quark with $p_{\mathrm{T}} > 50$ GeV at the parton level.

Event selection cutflows for signal samples with $m(\tilde{\chi}_{1}^0)$ = 150 GeV and $\Delta m(\tilde{\chi}_{1}^\pm, \tilde{\chi}_{1}^0)$ = 0.5, 0.35, and 0.25 GeV, including all six production processes ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$). The cross-section used to obtain the initial number of events ($\sigma(\mathrm{n}_{\mathrm{jets}}) \geq 1$) refers to an emission of at least one gluon or quark with $p_{\mathrm{T}} > 50$ GeV at the parton level.

Inclusive cross section predictions up to QCD NNLO accuracy using the NNPDF3.1 PDF set

Measured production cross sections ratio $\sigma(W^+ + \overline{c})$ / $\sigma(W^- + c)$

Predictions for the cross sections ratio $\sigma(W^+ + \overline{c})$ / $\sigma(W^- + c)$ at QCD NLO accuracy from MCFM using different PDF sets

Predictions for the cross sections ratio $\sigma(W^+ + \overline{c})$ / $\sigma(W^- + c)$ up to QCD NNLO accuracy using the NNPDF3.1 PDF set

Measured diferential cross sections $\sigma(W^- + c) + \sigma(W^+ + \overline{c})$ as a function of the absolute value of the pseudorapidity of the lepton from the W decay, unfolded to the particle level.

Measured diferential cross sections as a function of the transverse momentum of the lepton from the W decay, unfolded to the particle level.

Measured diferential cross sections $\sigma(W^- + c) + \sigma(W^+ + \overline{c})$ as a function of the absolute value of the pseudorapidity of the lepton from the W decay, unfolded to the parton level.

Measured diferential cross sections as a function of the transverse momentum of the lepton from the W decay, unfolded to the parton level.

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.

The signal cross-sections values of the signal QBH RS1 with n=1 extra dimensions, as a function of threshold mass

The product of acceptance and selection efficiency for QBH ADD model, as a function of threshold mass of the signal.

The product of acceptance and selection efficiency for QBH RS1 models, as a function of threshold mass of the signal.

The product of acceptance and selection efficiency for q* signal, as a function of resonance mass

The product of acceptance and selection efficiency for b* signal, as a function of resonance mass of the signal.

Distributions of the γ+jet invariant mass generated from various signal samples for reconstructed mass 4 TeV

Fitting distribution of data with expected q*, and QBH signal events, and fit parameters p0= 3.05674e+00, p1 = 10.5343, p3 = 4.15163 and p4 = 0.107405

Fitting distribution of data with expected b* events, and fit parameters p0= 1.45055e+03, p1 = 2.04830e+01, p3 = -4.16760e-01 and p4 = -5.07768e-01

Fitting distribution of data with expected b* events for 0btag category, and fit parameters p0= 2.44120e+00, p1 = 1.08886e+01, p3 = 4.23198e+00 and p4 = 1.16300e-01

Exclusion limits on the product of cross section and branching fraction for q* signal coupling f = 1.0, as a function of the resonance mass hypothesis.

Theoretical cross-section of q* signal for coupling multiplier f =1.0

Exclusion limits on the product of cross section and branching fraction for the q* signal coupling f = 0.5, as a function of the resonance mass hypothesis.

Theoretical cross-section of q* signal for coupling multiplier f =0.5

Exclusion limits on the product of cross section and branching fraction for q* coupling f = 0.1, as a function of the resonance mass hypothesis.

Theoretical cross-section of q* signal for coupling multiplier f =0.1

Exclusion limits on the product of cross section and branching fraction for b* signal coupling f = 1.0, as a function of the resonance mass hypothesis.

Theoretical cross-section of b* signal for coupling multiplier f =1.0

Exclusion limits on the product of cross section and branching fraction for b* signal coupling f = 0.5, as a function of the resonance mass hypothesis.

Theoretical cross-section of b* signal for coupling multiplier f =0.5

Exclusion limits on the product of cross section and branching fraction for b* signal coupling f = 0.1, as a function of the resonance mass hypothesis.

Theoretical cross-section of b* signal for coupling multiplier f =0.1

Exclusion limits on the product of cross section and branching fraction for QBH ADD signal, as a function of the mass hypothesis.

Theoretical cross-section of ADD signal

Exclusion limits on the product of cross section and branching fraction for QBH RS1 signal, as a function of the mass hypothesis.

Theoretical cross-section of RS1 signal

The expected and observed exclusion mass limits for q* and b* signals, as a function coupling multiplier

The observed exclusion mass limits for b* signal, as a function of threshold mass of the signal.

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.

Distribution of the MLP W+jets score in the CRs for the $T\overline{T}$ search. The observed data, predicted $T\overline{T}$ signal with mass of 1.2 (1.5) TeV in the singlet scenario, and the background are all shown. Statistical and systematic uncertainties in the background prediction before performing the fit to data are also shown.

Distribution of DeepAK8 jet tags in the DeepAK8 CR of the $T\overline{T}$ search. The observed data are shown using black markers, $T\overline{T}$ signals using solid lines, and background using filled histograms. Statistical and systematic uncertainties in the background prediction before performing the fit to data are shown by the hatched region.

Distribution of HT in the W+jets CR of the $T\overline{T}$ search. The observed data are shown using black markers, $T\overline{T}$ signals using solid lines, and background using filled histograms. Statistical and systematic uncertainties in the background prediction before performing the fit to data are shown by the hatched region.

Distribution of HT in the $T\overline{T}$ CR of the $T\overline{T}$ search. The observed data are shown using black markers, $T\overline{T}$ signals using solid lines, and background using filled histograms. Statistical and systematic uncertainties in the background prediction before performing the fit to data are shown by the hatched region.

Numbers of predicted and observed CR events in 2016--2018 data for the $T\overline{T}$ signal hypotheses in the single-lepton channel, after a background-only fit to data. Predicted numbers of signal events before the fit to data are included for comparison, using the singlet branching fraction scenario. Uncertainties include statistical and systematic components, and lepton flavor categories are combined with their uncertainties added in quadrature. Values in the DeepAK8 CR represent the number of large-radius jets rather than number of events.

Numbers of predicted and observed CR events in 2016--2018 data for the $B\overline{B}$ signal hypotheses in the single-lepton channel, after a background-only fit to data. Predicted numbers of signal events before the fit to data are included for comparison, using the singlet branching fraction scenario. Uncertainties include statistical and systematic components, and lepton flavor categories are combined with their uncertainties added in quadrature. Values in the DeepAK8 CR represent the number of large-radius jets rather than number of events.

Numbers of predicted and observed CR events in 2017--2018 data in the same-sign dilepton channel, after a background-only fit to data. Predicted numbers of signal events before the fit to data are included for comparison, using the singlet branching fraction scenario. Uncertainties include statistical and systematic components. Predictions for 2017 and 2018 are combined with their uncertainties added in quadrature.

Distribution of lepton $p_T$ in 2017 in the multilepton channel nonprompt lepton control region for all flavor categories, evaluated with the best-fit nonprompt rates. The uncertainty shown is the quadratic sum of statistical and systematics uncertainties.

Distribution of lepton $p_T$ in 2018 in the multilepton channel nonprompt lepton control region for all flavor categories, evaluated with the best-fit nonprompt rates. The uncertainty shown is the quadratic sum of statistical and systematics uncertainties.

Numbers of predicted and observed CR events in 2017--2018 data in the multilepton channel, after a background-only fit to data. Predicted numbers of signal events before the fit to data are included for comparison, using the singlet branching fraction scenario. Uncertainties include statistical and systematic components. Predictions for 2017 and 2018 are combined with their uncertainties added in quadrature.

Numbers of predicted and observed $T\overline{T}$ SR events in 2016--2018 data in the single-lepton channel, after a background-only fit to data. Predicted numbers of signal events before the fit to data are included for comparison, using the singlet branching fraction scenario. Uncertainties include statistical and systematic components, and lepton flavor categories are combined with their uncertainties added in quadrature.

Distribution of the VLQ score in single-lepton category 1. Observed data is shown using black markers, $T\overline{T}$ signal with mass of 1.2 (1.5) TeV in the singlet scenario using solid (dashed) lines, and post-fit background using filled histograms. Statistical and systematic uncertainties in the background prediction after performing the fit to data are shown by the hatched region. Electron and muon categories have been combined with their uncertainties added in quadrature.

Distribution of the VLQ score in single-lepton category 2. Observed data is shown using black markers, $T\overline{T}$ signal with mass of 1.2 (1.5) TeV in the singlet scenario using solid (dashed) lines, and post-fit background using filled histograms. Statistical and systematic uncertainties in the background prediction after performing the fit to data are shown by the hatched region. Electron and muon categories have been combined with their uncertainties added in quadrature.

Distribution of the VLQ score in single-lepton category 3. Observed data is shown using black markers, $T\overline{T}$ signal with mass of 1.2 (1.5) TeV in the singlet scenario using solid (dashed) lines, and post-fit background using filled histograms. Statistical and systematic uncertainties in the background prediction after performing the fit to data are shown by the hatched region. Electron and muon categories have been combined with their uncertainties added in quadrature.

Distribution of the VLQ score in single-lepton category 4. Observed data is shown using black markers, $T\overline{T}$ signal with mass of 1.2 (1.5) TeV in the singlet scenario using solid (dashed) lines, and post-fit background using filled histograms. Statistical and systematic uncertainties in the background prediction after performing the fit to data are shown by the hatched region. Electron and muon categories have been combined with their uncertainties added in quadrature.

Distribution of the VLQ score in single-lepton category 5. Observed data is shown using black markers, $T\overline{T}$ signal with mass of 1.2 (1.5) TeV in the singlet scenario using solid (dashed) lines, and post-fit background using filled histograms. Statistical and systematic uncertainties in the background prediction after performing the fit to data are shown by the hatched region. Electron and muon categories have been combined with their uncertainties added in quadrature.

Distribution of the VLQ score in single-lepton category 6. Observed data is shown using black markers, $T\overline{T}$ signal with mass of 1.2 (1.5) TeV in the singlet scenario using solid (dashed) lines, and post-fit background using filled histograms. Statistical and systematic uncertainties in the background prediction after performing the fit to data are shown by the hatched region. Electron and muon categories have been combined with their uncertainties added in quadrature.

Distribution of the VLQ score in single-lepton category 7. Observed data is shown using black markers, $T\overline{T}$ signal with mass of 1.2 (1.5) TeV in the singlet scenario using solid (dashed) lines, and post-fit background using filled histograms. Statistical and systematic uncertainties in the background prediction after performing the fit to data are shown by the hatched region. Electron and muon categories have been combined with their uncertainties added in quadrature.

Distribution of the VLQ score in single-lepton category 8. Observed data is shown using black markers, $T\overline{T}$ signal with mass of 1.2 (1.5) TeV in the singlet scenario using solid (dashed) lines, and post-fit background using filled histograms. Statistical and systematic uncertainties in the background prediction after performing the fit to data are shown by the hatched region. Electron and muon categories have been combined with their uncertainties added in quadrature.

Distribution of the VLQ score in single-lepton category 9. Observed data is shown using black markers, $T\overline{T}$ signal with mass of 1.2 (1.5) TeV in the singlet scenario using solid (dashed) lines, and post-fit background using filled histograms. Statistical and systematic uncertainties in the background prediction after performing the fit to data are shown by the hatched region. Electron and muon categories have been combined with their uncertainties added in quadrature.

Distribution of the VLQ score in single-lepton category 10. Observed data is shown using black markers, $T\overline{T}$ signal with mass of 1.2 (1.5) TeV in the singlet scenario using solid (dashed) lines, and post-fit background using filled histograms. Statistical and systematic uncertainties in the background prediction after performing the fit to data are shown by the hatched region. Electron and muon categories have been combined with their uncertainties added in quadrature.

Distribution of the VLQ score in single-lepton category 11. Observed data is shown using black markers, $T\overline{T}$ signal with mass of 1.2 (1.5) TeV in the singlet scenario using solid (dashed) lines, and post-fit background using filled histograms. Statistical and systematic uncertainties in the background prediction after performing the fit to data are shown by the hatched region. Electron and muon categories have been combined with their uncertainties added in quadrature.

Distribution of the VLQ score in single-lepton category 12. Observed data is shown using black markers, $T\overline{T}$ signal with mass of 1.2 (1.5) TeV in the singlet scenario using solid (dashed) lines, and post-fit background using filled histograms. Statistical and systematic uncertainties in the background prediction after performing the fit to data are shown by the hatched region. Electron and muon categories have been combined with their uncertainties added in quadrature.

Distribution of $H_T^{\mathrm{lep}}$ in the same-sign dilepton signal region for $ee$ category. Data from 2017 and 2018 is shown using black markers, $T\overline{T}$ signals with mass of 1.2 (1.5) TeV in the singlet scenario using solid (dashed) lines, and post-fit background using filled histograms. Statistical and systematic uncertainties in the background prediction after performing the fit to data are shown by the hatched region.

Distribution of $H_T^{\mathrm{lep}}$ in the same-sign dilepton signal region for $e\mu$ category. Data from 2017 and 2018 is shown using black markers, $T\overline{T}$ signals with mass of 1.2 (1.5) TeV in the singlet scenario using solid (dashed) lines, and post-fit background using filled histograms. Statistical and systematic uncertainties in the background prediction after performing the fit to data are shown by the hatched region.

Distribution of $H_T^{\mathrm{lep}}$ in the same-sign dilepton signal region for $\mu\mu$ category. Data from 2017 and 2018 is shown using black markers, $T\overline{T}$ signals with mass of 1.2 (1.5) TeV in the singlet scenario using solid (dashed) lines, and post-fit background using filled histograms. Statistical and systematic uncertainties in the background prediction after performing the fit to data are shown by the hatched region.

Distribution of $S_T$ in the multilepton signal region for $eee$ category. Data from 2017 and 2018 is shown using black markers, $T\overline{T}$ signals with mass of 1.2 (1.5) TeV in the singlet scenario using solid (dashed) lines, and post-fit background using filled histograms. Statistical and systematic uncertainties in the background prediction after performing the fit to data are shown by the hatched region.

Distribution of $S_T$ in the multilepton signal region for $ee\mu$ category. Data from 2017 and 2018 is shown using black markers, $T\overline{T}$ signals with mass of 1.2 (1.5) TeV in the singlet scenario using solid (dashed) lines, and post-fit background using filled histograms. Statistical and systematic uncertainties in the background prediction after performing the fit to data are shown by the hatched region.

Distribution of $S_T$ in the multilepton signal region for $e\mu\mu$ category. Data from 2017 and 2018 is shown using black markers, $T\overline{T}$ signals with mass of 1.2 (1.5) TeV in the singlet scenario using solid (dashed) lines, and post-fit background using filled histograms. Statistical and systematic uncertainties in the background prediction after performing the fit to data are shown by the hatched region.

Distribution of $S_T$ in the multilepton signal region for $\mu\mu\mu$ category. Data from 2017 and 2018 is shown using black markers, $T\overline{T}$ signals with mass of 1.2 (1.5) TeV in the singlet scenario using solid (dashed) lines, and post-fit background using filled histograms. Statistical and systematic uncertainties in the background prediction after performing the fit to data are shown by the hatched region.

Numbers of predicted and observed $B\overline{B}$ SR events in 2016--2018 data in the single-lepton channel, after a background-only fit to data. Predicted numbers of signal events before the fit to data are included for comparison, using the singlet branching fraction scenario. Uncertainties include statistical and systematic components, and lepton flavor categories are combined with their uncertainties added in quadrature.

Numbers of predicted and observed SR events in 2017--2018 data in the same-sign dilepton channel, after a background-only fit to data. Predicted numbers of signal events before the fit to data are included for comparison, using the singlet branching fraction scenario. Uncertainties include statistical and systematic components. Predictions for 2017 and 2018 are combined with their uncertainties added in quadrature.

Numbers of predicted and observed SR events in 2017--2018 data in the multilepton channel, after a background-only fit to data. Predicted numbers of signal events before the fit to data are included for comparison, using the singlet branching fraction scenario. Uncertainties include statistical and systematic components. Predictions for 2017 and 2018 are combined with their uncertainties added in quadrature.

Expected and observed lower limits on the VLT quark masses.

Expected and observed lower limits on the VLB quark masses.

Expected 95% CL upper limits on $T\overline{T}$ production cross sections for the singlet combination.

Expected 95% CL upper limits on $T\overline{T}$ production cross sections for the doublet combination.

Expected 95% CL upper limits on $B\overline{B}$ production cross sections for the singlet combination.

Expected 95% CL upper limits on $B\overline{B}$ production cross sections for the doublet combination.

The 95% CL expected lower mass limits on pair-produced T quark masses as functions of their branching ratios to W and H bosons.

The 95% CL observed lower mass limits on pair-produced T quark masses as functions of their branching ratios to W and H bosons.

The 95% CL expected lower mass limits on pair-produced B quark masses as functions of their branching ratios to W and H bosons.

The 95% CL observed lower mass limits on pair-produced B quark masses as functions of their branching ratios to W and H bosons.

Distribution of an input to the BDT classifier in the $3\ell$ category: The linear discrimminant $p_{T}^{miss,LD}$. The discriminant is defined by the relation $p_{T}^{miss,LD} = 0.6 p_{T}^{miss} + 0.4 H_{T}^{miss}$, where $H_{T}^{miss}$ corresponds to the magnitude of the vector $p_{T}$ sum of all electrons, muons, taus and small radius jets passing the selection critertia, and $p_{T}^{miss}$ represents the missing transverse momentum vector computed as the negative vector $p_{T}$ sum of all the particles reconstructed by the PF algorithm in the event.

Distributions of the transverse mass $m_{T}$ of the lepton that is not originating from the Z boson decay and the missing transverse momentum in the $3\ell$/WZ control region. The distributions expected for the WZ and ZZ as well as for other background processes are shown for the values of nuisance parameters obtained from the ML fit used in the signal extraction.

Distributions of the four lepton invariant mass $m_{4\ell}$ in the $4\ell$/ZZ control region. The distributions expected for the ZZ as well as for other background processes are shown for the values of nuisance parameters obtained from the ML fit used in the signal extraction.

Distributions of the transverse mass $m_{T}$ of the leading lepton and the missing transverse momentum in the $2\ell$(ss) control region. The distributions expected for the misidentified $\ell$ background as well as for other background processes is shown for the values of nuisance parameters obtained from the background-only ML fit, in which the HH signal is constrained to be zero.

Distributions of the reconstructed HH mass $m_{HH}$ in the $2\ell+2 au_{h}$ control region. The distributions expected for the misidentified $\ell/ au_{h}$ background as well as for other background processes is shown for the values of nuisance parameters obtained from the background-only ML fit, in which the HH signal is constrained to be zero.

Distribution in the output of the BDT trained for nonresonant HH production and evaluated for the benchmark scenario JHEP04 BM7 for the $2\ell$(ss) category. The SM HH signal is shown for a cross section amounting to $30$ times the value predicted in the SM. The distributions expected for the background processes are shown for the values of nuisance parameters obtained from the ML fit of the signal+background hypothesis to the data. The binning is chosen to approximate signal quantiles.

Distribution in the output of the BDT trained for nonresonant HH production and evaluated for the benchmark scenario JHEP04 BM7 for the $3\ell$ category. The SM HH signal is shown for a cross section amounting to $30$ times the value predicted in the SM. The distributions expected for the background processes are shown for the values of nuisance parameters obtained from the ML fit of the signal+background hypothesis to the data. The binning is chosen to approximate signal quantiles.

Distribution in the output of the BDT trained for nonresonant HH production and evaluated for the benchmark scenario JHEP04 BM7 for the $4\ell$ category. The SM HH signal is shown for a cross section amounting to $30$ times the value predicted in the SM. The distributions expected for the background processes are shown for the values of nuisance parameters obtained from the ML fit of the signal+background hypothesis to the data. The binning is chosen to approximate signal quantiles.

Distribution in the output of the BDT trained for nonresonant HH production and evaluated for the benchmark scenario JHEP04 BM7 for the $3\ell+1 au_{h}$ category. The SM HH signal is shown for a cross section amounting to $30$ times the value predicted in the SM. The distributions expected for the background processes are shown for the values of nuisance parameters obtained from the ML fit of the signal+background hypothesis to the data. The binning is chosen to approximate background quantiles.

Distribution in the output of the BDT trained for nonresonant HH production and evaluated for the benchmark scenario JHEP04 BM7 for the $2\ell+2 au_{h}$ category. The SM HH signal is shown for a cross section amounting to $30$ times the value predicted in the SM. The distributions expected for the background processes are shown for the values of nuisance parameters obtained from the ML fit of the signal+background hypothesis to the data. The binning is chosen to approximate background quantiles.

Distribution in the output of the BDT trained for nonresonant HH production and evaluated for the benchmark scenario JHEP04 BM7 for the $1\ell+3 au_{h}$ category. The SM HH signal is shown for a cross section amounting to $30$ times the value predicted in the SM. The distributions expected for the background processes are shown for the values of nuisance parameters obtained from the ML fit of the signal+background hypothesis to the data. The binning is chosen to approximate background quantiles.

Distribution in the output of the BDT trained for nonresonant HH production and evaluated for the benchmark scenario JHEP04 BM7 for the $4 au_{h}$ category. The SM HH signal is shown for a cross section amounting to $30$ times the value predicted in the SM. The distributions expected for the background processes are shown for the values of nuisance parameters obtained from the ML fit of the signal+background hypothesis to the data. The binning is chosen to approximate background quantiles.

Observed and expected $95\%$ CL upper limits on the SM HH production cross section, obtained for both individual search categories and from a simultaneous fit of all seven categories combined.

Observed and expected $95\%$ CL upper limits on the HH production cross section as a function of the Higgs boson self-coupling strength modifier $\kappa_\lambda$ for the combination of all seven categories. All Higgs boson couplings other than $\lambda$ are assumed to have the values predicted in the SM.

Observed and expected $95\%$ CL upper limits on the HH production cross section as a function of the Higgs boson self-coupling strength modifier $\kappa_\lambda$ for the seven different categories as well as their combination. All Higgs boson couplings other than $\lambda$ are assumed to have the values predicted in the SM.

Observed and expected $95\%$ CL upper limits on the HH production cross section for the twelve benchmark scenarios from doi:10.1007/JHEP04(2016)126, the additional benchmark scenario 8a from doi:10.1007/JHEP09(2018)057, the seven benchmark scenarios from doi:10.1007/JHEP03(2020)091, and for the SM.

Observed and expected $95\%$ CL upper limits on the HH production cross section for the twelve benchmark scenarios from doi:10.1007/JHEP04(2016)126, the additional benchmark scenario 8a from doi:10.1007/JHEP09(2018)057, the seven benchmark scenarios from doi:10.1007/JHEP03(2020)091, and for the SM. The limits are shown for all seven search categories as well as for their combination.

Observed and expected $95\%$ CL upper limits on the HH production cross section as a function of the effective coupling $c_{2}$ for the combination of all seven categories. All Higgs boson couplings other than $c_{2}$ are assumed to have the values predicted in the SM.

Observed and expected $95\%$ CL upper limits on the HH production cross section as a function of the effective coupling $c_{2}$ and the top Yukawa coupling modifier $\kappa_{t}$ for the combination of all seven categories. All Higgs boson couplings other than $c_{2}$ and $\kappa_{t}$ are assumed to have the values predicted in the SM. The position of the SM in the ($c_{2}-\kappa_{t}$) plane, as well as the best fit value of $(c_{2},\kappa_{t})=(1.05, 1.74)$ together with contours for the theory cross section are shown as well.

Observed and expected $95\%$ CL upper limits on the HH production cross section as a function of the Higgs boson self-coupling modifier $\kappa_{\lambda}$ and the top Yukawa coupling modifier $\kappa_{t}$ for the combination of all seven categories. All Higgs boson couplings other than $\kappa_{\lambda}$ and $\kappa_{t}$ are assumed to have the values predicted in the SM. The position of the SM in the ($\kappa_{\lambda}-\kappa_{t}$) plane, as well as the best fit value of $(\kappa_{\lambda},\kappa_{t})=(-3.54, -1.70)$ together with contours for the theory cross section are shown as well.

Observed and expected $95\%$ CL upper limits on the HH production cross section as a function of the effective coupling $c_{2}$ and the Higgs boson self-coupling modifier $\kappa_{\lambda}$ for the combination of all seven categories. All Higgs boson couplings other than $c_{2}$ and $\kappa_{\lambda}$ are assumed to have the values predicted in the SM. The position of the SM in the ($c_{2}-\kappa_{\lambda}$) plane, as well as the best fit value of $(c_{2},\kappa_{\lambda})=(-0.66, 5.33)$ together with contours for the theory cross section are shown as well.

Observed and expected $95\%$ CL upper limits on the production of new particles X of spin $0$ and mass $m_{X}$ in the range $250$-$1000$ GeV, which decay to Higgs boson pairs.

Observed and expected $95\%$ CL upper limits on the production of new particles X of spin $0$ and mass $m_{X}$ in the range $250$-$1000$ GeV, which decay to Higgs boson pairs. The Limit is shown for the seven different search categories as well as their combination.

Observed and expected $95\%$ CL upper limits on the production of new particles X of spin $2$ and mass $m_{X}$ in the range $250$-$1000$ GeV, which decay to Higgs boson pairs.

Observed and expected $95\%$ CL upper limits on the production of new particles X of spin $2$ and mass $m_{X}$ in the range $250$-$1000$ GeV, which decay to Higgs boson pairs. The Limit is shown for the seven different search categories as well as their combination.

Distribution in the output of the BDT trained for resonances of spin 2 and mass $750\,$GeV production for the $2\ell$(ss) category. The resonant HH signal is shown for a cross section amounting to $1\,$pb. The distributions expected for the background processes are shown for the values of nuisance parameters obtained from the ML fit of the signal+background hypothesis to the data. The binning is chosen to approximate signal quantiles.

Distribution in the output of the BDT trained for resonances of spin 2 and mass $750\,$GeV production for the $3\ell$ category. The resonant HH signal is shown for a cross section amounting to $1\,$pb. The distributions expected for the background processes are shown for the values of nuisance parameters obtained from the ML fit of the signal+background hypothesis to the data. The binning is chosen to approximate signal quantiles.

The observed and expected (in parentheses) 95% CL lower mass limits on RPV SUSY, Z′ ($\mathcal{B}=0.1$) , and QBH signals for the e$\mu$, e$\tau$, and $\mu\tau$ channels.

Expected and observed 95% CL upper limits on the product of cross section times branching fraction as a function of the $ au$ sneutrino mass in an RPV SUSY model for the e$\mu$ channel. The shaded bands represent the one and two standard deviation (s.d.) uncertainties in the expected limits. The red and blue solid lines show the product of cross section times branching fraction as a function of the tau sneutrino mass for two different values of couplings.

Expected and observed 95% CL upper limits on the product of cross section times branching fraction as a function of the $ au$ sneutrino mass in an RPV SUSY model for the e$\tau$ channel. The shaded bands represent the one and two standard deviation (s.d.) uncertainties in the expected limits. The red and blue solid lines show the product of cross section times branching fraction as a function of the tau sneutrino mass for two different values of couplings.

Expected and observed 95% CL upper limits on the product of cross section times branching fraction as a function of the $ au$ sneutrino mass in an RPV SUSY model for the $\mu\tau$ channel. The shaded bands represent the one and two standard deviation (s.d.) uncertainties in the expected limits. The red and blue solid lines show the product of cross section times branching fraction as a function of the tau sneutrino mass for two different values of couplings.

Expected (black dashed line) and observed (black solid line) 95% CL upper limits on the product of cross section and branching fraction for a Z′ ($\mathcal{B}=0.1$) boson with LFV decays, in the e$\mu$ channel.The shaded bands represent the one and two standard deviation (s.d.) uncertainties in the expected limits. The red solid lines show the product of cross section times branching fraction as a function of the Z′ mass.

Expected (black dashed line) and observed (black solid line) 95% CL upper limits on the product of cross section and branching fraction for a Z′ ($\mathcal{B}=0.1$) boson with LFV decays, in the e$\tau$ channel.The shaded bands represent the one and two standard deviation (s.d.) uncertainties in the expected limits. The red solid lines show the product of cross section times branching fraction as a function of the Z′ mass.

Expected (black dashed line) and observed (black solid line) 95% CL upper limits on the product of cross section and branching fraction for a Z′ ($\mathcal{B}=0.1$) boson with LFV decays, in the $\mu\tau$ channel.The shaded bands represent the one and two standard deviation (s.d.) uncertainties in the expected limits. The red solid lines show the product of cross section times branching fraction as a function of the Z′ mass.

Expected (black dashed line) and observed (black solid line) 95% CL upper limits on the product of cross section and branching fraction for quantum black hole production in an ADD model with $n=4$ extra dimensions, in the e$\mu$ channel. The shaded bands represent the one and two standard deviation (s.d.) uncertainties in the expected limits. The red solid lines show the product of cross section times branching fraction as a function of the QBH threshold mass.

Expected (black dashed line) and observed (black solid line) 95% CL upper limits on the product of cross section and branching fraction for quantum black hole production in an ADD model with $n=4$ extra dimensions, in the e$\tau$ channel. The shaded bands represent the one and two standard deviation (s.d.) uncertainties in the expected limits. The red solid lines show the product of cross section times branching fraction as a function of the QBH threshold mass.

Expected (black dashed line) and observed (black solid line) 95% CL upper limits on the product of cross section and branching fraction for quantum black hole production in an ADD model with $n=4$ extra dimensions, in the $\mu\tau$ channel. The shaded bands represent the one and two standard deviation (s.d.) uncertainties in the expected limits. The red solid lines show the product of cross section times branching fraction as a function of the QBH threshold mass.

Upper limits at 95% CL on the RPV SUSY model in the plane of $\tau$ sneutrino mass and $\lambda'$ coupling, for four values of $\lambda$ couplings for the e$\mu$ channel. The regions to the left of and above the curves are excluded.

Upper limits at 95% CL on the RPV SUSY model in the plane of $\tau$ sneutrino mass and $\lambda'$ coupling, for four values of $\lambda$ couplings for the e$\tau$ channel. The regions to the left of and above the curves are excluded.

Upper limits at 95% CL on the RPV SUSY model in the plane of $\tau$ sneutrino mass and $\lambda'$ coupling, for four values of $\lambda$ couplings for the $\mu\tau$ channel. The regions to the left of and above the curves are excluded.

Model-independent upper limits at 95% CL on the product of cross section, branching fraction, and acceptance are shown. Observed (expected) limits are shown in black solid (dashed) lines for the e$\mu$ channel. The shaded bands represent the one and two standard deviation (s.d.) uncertainties in the expected limits.

Model-independent upper limits at 95% CL on the product of cross section, branching fraction, and acceptance are shown. Observed (expected) limits are shown in black solid (dashed) lines for the e$\tau$ channel. The shaded bands represent the one and two standard deviation (s.d.) uncertainties in the expected limits.

Model-independent upper limits at 95% CL on the product of cross section, branching fraction, and acceptance are shown. Observed (expected) limits are shown in black solid (dashed) lines for the $\mu\tau$ channel. The shaded bands represent the one and two standard deviation (s.d.) uncertainties in the expected limits.

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 "channel_year_binnumber", following the binning from Figure 2.

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 "channel_year_binnumber", following the binning from Figure 2.

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 "channel_year_binnumber", following the binning from Figure 2.

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 "channel_year_binnumber", following the binning used in Figure 2.

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 "channel_year_binnumber", following the binning used in Figure 2.

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 "channel_year_binnumber", following the binning used in Figure 2.