Corrected $m(HH)$ distribution in the resolved $4b$ signal region (dots), after the fit under the background-only hypothesis. The error bars on the $4b$ points represent the Poisson uncertainties corresponding to their event yields. The background model (teal histogram) is shown with its total post-fit uncertainty (gray band). The final bin includes overflow. Representative spin-0 signal hypotheses (dashed, dotted, and dashed-dotted lines) are overlaid, normalized to the overall expected limits on their cross-sections. The bottom panel shows the difference between the $4b$ distribution and the background model, relative to the background model. No significant excess of data relative to the SM background is observed.

Corrected $m(HH)$ distribution in the resolved $4b$ signal region (dots), after the fit under the background-only hypothesis. The error bars on the $4b$ points represent the Poisson uncertainties corresponding to their event yields. The background model (teal histogram) is shown with its total post-fit uncertainty (gray band). The final bin includes overflow. Representative spin-2 signal hypotheses (dashed, dotted, and dashed-dotted lines) are overlaid, normalized to the overall expected limits on their cross-sections. The bottom panel shows the difference between the $4b$ distribution and the background model, relative to the background model. No significant excess of data relative to the SM background is observed.

Cumulative signal acceptance times efficiency as a function of the resonance mass for various selection steps in the boosted channel. The steps up to the $b$-tag categorization are shown for the spin-0.

Cumulative signal acceptance times efficiency as a function of the resonance mass for various selection steps in the boosted channel. The steps up to the $b$-tag categorization are shown for the spin-2.

Cumulative signal acceptance times efficiency as a function of the resonance mass for various selection steps in the boosted channel. The efficiencies of the three b-tag categories are shown for the spin-0 scenario; this efficiency is obtained after the other selection steps including the SR definition. The signal efficiency in the 4b region has a maximum around 1.5 TeV. Above that value the track-jets start to merge together, and for the highest resonance masses the 2b category becomes the most efficient.

Cumulative signal acceptance times efficiency as a function of the resonance mass for various selection steps in the boosted channel. The efficiencies of the three b-tag categories are shown for the spin-2 scenario; this efficiency is obtained after the other selection steps including the SR definition. The signal efficiency in the 4b region has a maximum around 1.5 TeV. Above that value the track-jets start to merge together, and for the highest resonance masses the 2b category becomes the most efficient.

Comparison of the background model (stacked histograms) with data (dots) in the $2b$ validation region. The error bars on the data points represent the Poisson uncertainties corresponding to their event yields. The background uncertainty (gray band) is computed by adding all individual components in quadrature and is not allowed to extend below zero.

Comparison of the background model (stacked histograms) with data (dots) in the $3b$ validation region. The error bars on the data points represent the Poisson uncertainties corresponding to their event yields. The background uncertainty (gray band) is computed by adding all individual components in quadrature and is not allowed to extend below zero.

Comparison of the background model (stacked histograms) with data (dots) in the $4b$ validation region. The error bars on the data points represent the Poisson uncertainties corresponding to their event yields. The background uncertainty (gray band) is computed by adding all individual components in quadrature and is not allowed to extend below zero.

The $m(HH)$ distributions in the boosted $2b$ signal regions (dots), after the fit under the background-only hypothesis. The error bars on the data points represent the Poisson uncertainties corresponding to their event yields. The background model (stacked histogram) is shown with its total post-fit uncertainty (gray band). The uncertainty bands are defined using an ensemble of curves constructed by sampling a multivariate Gaussian probability density function built from the covariance matrix of the fit. Representative spin-0 signal hypotheses (dashed and dashed-dotted lines) are overlaid, normalized to the overall expected limits on their cross-sections. No significant excess of data relative to the SM background is observed.

The $m(HH)$ distributions in the boosted $2b$ signal regions (dots), after the fit under the background-only hypothesis. The error bars on the data points represent the Poisson uncertainties corresponding to their event yields. The background model (stacked histogram) is shown with its total post-fit uncertainty (gray band). The uncertainty bands are defined using an ensemble of curves constructed by sampling a multivariate Gaussian probability density function built from the covariance matrix of the fit. Representative spin-2 signal hypotheses (dashed and dashed-dotted lines) are overlaid, normalized to the overall expected limits on their cross-sections. No significant excess of data relative to the SM background is observed.

The $m(HH)$ distributions in the boosted $3b$ signal regions (dots), after the fit under the background-only hypothesis. The error bars on the data points represent the Poisson uncertainties corresponding to their event yields. The background model (stacked histogram) is shown with its total post-fit uncertainty (gray band). The uncertainty bands are defined using an ensemble of curves constructed by sampling a multivariate Gaussian probability density function built from the covariance matrix of the fit. Representative spin-0 signal hypotheses (dashed and dashed-dotted lines) are overlaid, normalized to the overall expected limits on their cross-sections. No significant excess of data relative to the SM background is observed.

The $m(HH)$ distributions in the boosted $3b$ signal regions (dots), after the fit under the background-only hypothesis. The error bars on the data points represent the Poisson uncertainties corresponding to their event yields. The background model (stacked histogram) is shown with its total post-fit uncertainty (gray band). The uncertainty bands are defined using an ensemble of curves constructed by sampling a multivariate Gaussian probability density function built from the covariance matrix of the fit. Representative spin-2 signal hypotheses (dashed and dashed-dotted lines) are overlaid, normalized to the overall expected limits on their cross-sections. No significant excess of data relative to the SM background is observed.

The $m(HH)$ distributions in the boosted $4b$ signal regions (dots), after the fit under the background-only hypothesis. The error bars on the data points represent the Poisson uncertainties corresponding to their event yields. The background model (stacked histogram) is shown with its total post-fit uncertainty (gray band). The uncertainty bands are defined using an ensemble of curves constructed by sampling a multivariate Gaussian probability density function built from the covariance matrix of the fit. Representative spin-0 signal hypotheses (dashed and dashed-dotted lines) are overlaid, normalized to the overall expected limits on their cross-sections. No significant excess of data relative to the SM background is observed.

The $m(HH)$ distributions in the boosted $4b$ signal regions (dots), after the fit under the background-only hypothesis. The error bars on the data points represent the Poisson uncertainties corresponding to their event yields. The background model (stacked histogram) is shown with its total post-fit uncertainty (gray band). The uncertainty bands are defined using an ensemble of curves constructed by sampling a multivariate Gaussian probability density function built from the covariance matrix of the fit. Representative spin-2 signal hypotheses (dashed and dashed-dotted lines) are overlaid, normalized to the overall expected limits on their cross-sections. No significant excess of data relative to the SM background is observed.

Expected (dashed black lines) and observed (solid black lines) 95% CL upper limits on the cross-section of resonant $HH$ production in the spin-0 signal models. The $\pm 1 \sigma$ and $\pm 2 \sigma$ uncertainty ranges for the expected limits (colored bands) are shown. Expected limits using each of the resolved and boosted channels individually (dashed colored lines) are shown. The nominal $H\rightarrow b\bar{b}$ branching ratio is taken as 0.582.

Expected (dashed black lines) and observed (solid black lines) 95% CL upper limits on the cross-section of resonant $HH$ production in the spin-2 signal models. The $\pm 1 \sigma$ and $\pm 2 \sigma$ uncertainty ranges for the expected limits (colored bands) are shown. Expected limits using each of the resolved and boosted channels individually (dashed colored lines) are shown. The theoretical prediction for the bulk RS model with $k/\bar{M}_{\text{Pl}} = 1$ (solid red line) is shown; the decrease below 350 GeV is due to a sharp reduction in the $G^{*}_{\text{KK}} \rightarrow HH$ branching ratio. The nominal $H\rightarrow b\bar{b}$ branching ratio is taken as 0.582.

Distribution of $m_{\mathrm{T},3l}$ in the JNLow SR after the background-only fit. The uncertainty on the expected number of background events includes all statistical and systematic post-fit uncertainties with the correlations between various background sources taken into account.

Distribution of $H_\text{T} + E_\text{T}^\text{miss}$ in the Q0 SR after the background-only fit. The uncertainty on the expected number of background events includes all statistical and systematic post-fit uncertainties with the correlations between various background sources taken into account.

Distribution of $H_\text{T} + E_\text{T}^\text{miss}$ in the Q2 SR after the background-only fit. The uncertainty on the expected number of background events includes all statistical and systematic post-fit uncertainties with the correlations between various background sources taken into account.

Distribution of $m_{\mathrm{T},3l}$ in the ZL-CR after the background-only fit.

Distribution of $m_{\mathrm{T},3l}$ in the Fake-CR after the background-only fit.

Distribution of $H_\text{T} + E_\text{T}^\text{miss}$ in the Q0 DB-CR after the background-only fit.

Distribution of $H_\text{T} + E_\text{T}^\text{miss}$ in the Q0 RT-CR after the background-only fit.

Expected and observed exclusion limit for the combination of the two- (from Ref. EXOT-2018-33), three- and four-lepton channels, for the type-III seesaw process with the corresponding one- and two-standard-deviation uncertainty bands, showing the 95% CL upper limit on the cross-section.

Expected and observed 95% ( $CL_s$ ) exclusion limits in the three lepton channel for the type-III seesaw process with the corresponding one- and two-standard-deviation bands, showing the 95% CL upper limit on the cross-section.

Expected and observed 95% ( $CL_s$ ) exclusion limits in the four lepton channel for the type-III seesaw process with the corresponding one- and two-standard-deviation bands, showing the 95% CL upper limit on the cross-section.

Cross-sections of signal Monte Carlo samples for each mass point considered in this analysis. Leading order cross-sections ( $\sigma_{LO}$ ) are computed by the generator and then rescaled to next-to-leading cross-sections ( $\sigma_{NLO+NLL}$ ), with their corresponding uncertainties, using information taken from Refs. C1C1 and N2C1.

Expected signal and background yields after each of the analysis selection cuts for the 800 GeV mass hypothesis in the ZL SR. Preselection represents events with at least three leptons.

Expected signal and background yields after each of the analysis selection cuts for the 800 GeV mass hypothesis in the ZLVeto SR. Preselection represents events with at least three leptons.

Expected signal and background yields after each of the analysis selection cuts for the 800 GeV mass hypothesis in the JNLow SR. Preselection represents events with at least three leptons.

Expected signal and background yields after each of the analysis selection cuts for the 800 GeV mass hypothesis in the Q0 SR. Preselection represents events with at least three leptons.

Expected signal and background yields after each of the analysis selection cuts for the 800 GeV mass hypothesis in the Q2 SR. Preselection represents events with at least three leptons.

Expected signal and background yields after each of the analysis selection cuts for the 800 GeV mass hypothesis in the ZL CR. Preselection represents events with at least three leptons.

Expected signal and background yields after each of the analysis selection cuts for the 800 GeV mass hypothesis in the Q0-DB CR. Preselection represents events with at least three leptons.

Expected signal and background yields after each of the analysis selection cuts for the 800 GeV mass hypothesis in the Q0-RT CR. Preselection represents events with at least three leptons.

Expected background yields and observed data after the background-only fit, in the three-lepton CRs and VRs.

Expected background yields and observed data after the background-only fit, in the four-lepton CRs and VRs.

Expected and observed 95% ( $CL_s$ ) exclusion limits in the three and four lepton channels for the type-III seesaw process with the corresponding one- and two-standard-deviation bands, showing the 95% CL upper limit on the cross-section.

The Bose-Einstein correlation (BEC) parameter R as a function of n_ch for HMT events using different MC generators in the calculation of R₂(Q). The uncertainties shown are statistical. The lower panel of each plot shows the ratio of the BEC parameters obtained using EPOS LHC (red circles), Pythia 8 Monash (blue squares) and Herwig++ UE-EE-5 (green triangles) compared with the parameters obtained using Pythia 8 A2. The gray band in the lower panels is the MC systematic uncertainty, obtained as explained in the text.

The Bose-Einstein correlation (BEC) parameter R as a function of k_T for MB events using different MC generators in the calculation of R₂(Q). The uncertainties shown are statistical. The lower panel of each plot shows the ratio of the BEC parameters obtained using EPOS LHC (red circles), Pythia 8 Monash (blue squares) and Herwig++ UE-EE-5 (green triangles) compared with the parameters obtained using Pythia 8 A2. The gray band in the lower panels is the MC systematic uncertainty, obtained as explained in the text.

The Bose-Einstein correlation (BEC) parameter λ as a function of k_T for MB events using different MC generators in the calculation of R₂(Q). The uncertainties shown are statistical. The lower panel of each plot shows the ratio of the BEC parameters obtained using EPOS LHC (red circles), Pythia 8 Monash (blue squares) and Herwig++ UE-EE-5 (green triangles) compared with the parameters obtained using Pythia 8 A2. The gray band in the lower panels is the MC systematic uncertainty, obtained as explained in the text.

The two-particle double-ratio correlation function, R₂(Q), for pp collisions for track p_T >100 MeV at √s=13 TeV in the multiplicity interval 71 ≤ n_ch < 80 for the minimum-bias (MB) events. The blue dashed and red solid lines show the results of the exponential and Gaussian fits, respectively. The region excluded from the fits is shown. The statistical uncertainty and the systematic uncertainty for imperfections in the data reconstruction procedure are added in quadrature.

The two-particle double-ratio correlation function, R₂(Q), for pp collisions for track p_T >100 MeV at √s=13 TeV in the multiplicity interval 231 ≤ n_ch < 300 for the high-multiplicity track (HMT) events. The blue dashed and red solid lines show the results of the exponential and Gaussian fits, respectively. The region excluded from the fits is shown. The statistical uncertainty and the systematic uncertainty for imperfections in the data reconstruction procedure are added in quadrature.

The dependence of the correlation strength, λ(m_ch), on rescaled multiplicity, m_ch, obtained from the exponential fit of the R₂(Q) correlation functions for tracks with p_T > 100  MeV and p_T > 500 MeV at √s = 13  TeV for the minimum-bias (MB) and high multiplicity track (HMT) data. The uncertainties represent the sum in quadrature of the statistical and asymmetric systematic contributions. The black and blue solid curves represent the exponential fit of λ(m_ch) for p_T >100 MeV and p_T >500 MeV, respectively.

The dependence of the correlation strength, λ(m_ch), on rescaled multiplicity, m_ch, obtained from the exponential fit of the R₂(Q) correlation functions for tracks with p_T > 100  MeV and p_T > 500 MeV at √s = 13  TeV for the minimum-bias (MB) and high multiplicity track (HMT) data. The uncertainties represent the sum in quadrature of the statistical and asymmetric systematic contributions. The black and blue solid curves represent the exponential fit of λ(m_ch) for p_T >100 MeV and p_T >500 MeV, respectively.

The dependence of the correlation strength, λ(m_ch), on rescaled multiplicity, m_ch, obtained from the exponential fit of the R₂(Q) correlation functions for tracks with p_T > 100  MeV and p_T > 500 MeV at √s = 13  TeV for the minimum-bias (MB) and high multiplicity track (HMT) data. The uncertainties represent the sum in quadrature of the statistical and asymmetric systematic contributions. The black and blue solid curves represent the exponential fit of λ(m_ch) for p_T >100 MeV and p_T >500 MeV, respectively.

The dependence of the correlation strength, λ(m_ch), on rescaled multiplicity, m_ch, obtained from the exponential fit of the R₂(Q) correlation functions for tracks with p_T > 100  MeV and p_T > 500 MeV at √s = 13  TeV for the minimum-bias (MB) and high multiplicity track (HMT) data. The uncertainties represent the sum in quadrature of the statistical and asymmetric systematic contributions. The black and blue solid curves represent the exponential fit of λ(m_ch) for p_T >100 MeV and p_T >500 MeV, respectively.

The dependence of the source radius, R(m_ch), on m_ch. The uncertainties represent the sum in quadrature of the statistical and asymmetric systematic contributions. The black and blue solid curves represent the fit of R(m_ch) for ∛m_ch < 1.2 for p_T >100 MeV and p_T >500 MeV, respectively. The black and blue dotted curves are extensions of the black and blue solid curves beyond ∛m_ch > 1.2, respectively. The black and brown dashed curves represent the saturation value of R(m_ch) for ∛m_ch > 1.45 with p_T >100 MeV and for ∛m_ch > 1.6 with p_T >500 MeV, respectively.

The dependence of the source radius, R(m_ch), on m_ch. The uncertainties represent the sum in quadrature of the statistical and asymmetric systematic contributions. The black and blue solid curves represent the fit of R(m_ch) for ∛m_ch < 1.2 for p_T >100 MeV and p_T >500 MeV, respectively. The black and blue dotted curves are extensions of the black and blue solid curves beyond ∛m_ch > 1.2, respectively. The black and brown dashed curves represent the saturation value of R(m_ch) for ∛m_ch > 1.45 with p_T >100 MeV and for ∛m_ch > 1.6 with p_T >500 MeV, respectively.

The dependence of the source radius, R(m_ch), on m_ch. The uncertainties represent the sum in quadrature of the statistical and asymmetric systematic contributions. The black and blue solid curves represent the fit of R(m_ch) for ∛m_ch < 1.2 for p_T >100 MeV and p_T >500 MeV, respectively. The black and blue dotted curves are extensions of the black and blue solid curves beyond ∛m_ch > 1.2, respectively. The black and brown dashed curves represent the saturation value of R(m_ch) for ∛m_ch > 1.45 with p_T >100 MeV and for ∛m_ch > 1.6 with p_T >500 MeV, respectively.

The dependence of the source radius, R(m_ch), on m_ch. The uncertainties represent the sum in quadrature of the statistical and asymmetric systematic contributions. The black and blue solid curves represent the fit of R(m_ch) for ∛m_ch < 1.2 for p_T >100 MeV and p_T >500 MeV, respectively. The black and blue dotted curves are extensions of the black and blue solid curves beyond ∛m_ch > 1.2, respectively. The black and brown dashed curves represent the saturation value of R(m_ch) for ∛m_ch > 1.45 with p_T >100 MeV and for ∛m_ch > 1.6 with p_T >500 MeV, respectively.

The dependence of the R(m_ch) on ∛m_ch. The uncertainties represent the sum in quadrature of the statistical and asymmetric systematic contributions. The black and blue solid curves represent the fit of R(m_ch) for ∛m_ch < 1.2 for p_T >100 MeV and p_T >500 MeV, respectively. The black and blue dotted curves are extensions of the black and blue solid curves beyond ∛m_ch > 1.2, respectively. The black and brown dashed curves represent the saturation value of R(m_ch) for ∛m_ch > 1.45 with p_T >100 MeV and for ∛m_ch > 1.6 with p_T >500 MeV, respectively

The dependence of the R(m_ch) on ∛m_ch. The uncertainties represent the sum in quadrature of the statistical and asymmetric systematic contributions. The black and blue solid curves represent the fit of R(m_ch) for ∛m_ch < 1.2 for p_T >100 MeV and p_T >500 MeV, respectively. The black and blue dotted curves are extensions of the black and blue solid curves beyond ∛m_ch > 1.2, respectively. The black and brown dashed curves represent the saturation value of R(m_ch) for ∛m_ch > 1.45 with p_T >100 MeV and for ∛m_ch > 1.6 with p_T >500 MeV, respectively

The dependence of the R(m_ch) on ∛m_ch. The uncertainties represent the sum in quadrature of the statistical and asymmetric systematic contributions. The black and blue solid curves represent the fit of R(m_ch) for ∛m_ch < 1.2 for p_T >100 MeV and p_T >500 MeV, respectively. The black and blue dotted curves are extensions of the black and blue solid curves beyond ∛m_ch > 1.2, respectively. The black and brown dashed curves represent the saturation value of R(m_ch) for ∛m_ch > 1.45 with p_T >100 MeV and for ∛m_ch > 1.6 with p_T >500 MeV, respectively

The dependence of the R(m_ch) on ∛m_ch. The uncertainties represent the sum in quadrature of the statistical and asymmetric systematic contributions. The black and blue solid curves represent the fit of R(m_ch) for ∛m_ch < 1.2 for p_T >100 MeV and p_T >500 MeV, respectively. The black and blue dotted curves are extensions of the black and blue solid curves beyond ∛m_ch > 1.2, respectively. The black and brown dashed curves represent the saturation value of R(m_ch) for ∛m_ch > 1.45 with p_T >100 MeV and for ∛m_ch > 1.6 with p_T >500 MeV, respectively

Comparison of single-ratio two-particle correlation functions, using the unlike-charge particle (UCP) pair reference sample, for minimum-bias (MB) events, showing C₂^data(Q) (top panel) at 13 TeV (black circles) and 7 TeV (open blue circles), and the ratio of C₂^7 TeV (Q) to C₂^13 TeV (Q) (bottom panel). Comparison of C₂^data (Q) for representative multiplicity region 3.09 < m_ch ≤ 3.86. The statistical and systematic uncertainties, combined in quadrature, are presented. The systematic uncertainties include track efficiency, Coulomb correction, non-closure and multiplicity-unfolding uncertainties.

Comparison of single-ratio two-particle correlation functions, using the unlike-charge particle (UCP) pair reference sample, for minimum-bias (MB) events, showing C₂^data(Q) (top panel) at 13  TeV (black circles) and 7  TeV (open blue circles), and the ratio of C₂^7 TeV (Q) to C₂^13 TeV (Q) (bottom panel). Comparison of C₂^data (Q) for representative k_T region 400 < k_T ≤500  MeV. The statistical and systematic uncertainties, combined in quadrature, are presented. The systematic uncertainties include track efficiency, Coulomb correction, non-closure and multiplicity-unfolding uncertainties.

The k_T dependence of the correlation strength, λ(k_T), obtained from the exponential fit to the R₂(Q) correlation functions for events with multiplicity n_ch ≥ 2 and transfer momentum of tracks with p_T >100 MeV and p_T >500 MeV at √s=13 TeV for the minimum-bias (MB) and high-multiplicity track (HMT) events. The uncertainties represent the sum in quadrature of the statistical and systematic contributions. The curves represent the exponential fits to λ(k_T).

The k_T dependence of the correlation strength, λ(k_T), obtained from the exponential fit to the R₂(Q) correlation functions for events with multiplicity n_ch ≥ 2 and transfer momentum of tracks with p_T >100 MeV and p_T >500 MeV at √s=13 TeV for the minimum-bias (MB) and high-multiplicity track (HMT) events. The uncertainties represent the sum in quadrature of the statistical and systematic contributions. The curves represent the exponential fits to λ(k_T).

The k_T dependence of the correlation strength, λ(k_T), obtained from the exponential fit to the R₂(Q) correlation functions for events with multiplicity n_ch ≥ 2 and transfer momentum of tracks with p_T >100 MeV and p_T >500 MeV at √s=13 TeV for the minimum-bias (MB) and high-multiplicity track (HMT) events. The uncertainties represent the sum in quadrature of the statistical and systematic contributions. The curves represent the exponential fits to λ(k_T).

The k_T dependence of the correlation strength, λ(k_T), obtained from the exponential fit to the R₂(Q) correlation functions for events with multiplicity n_ch ≥ 2 and transfer momentum of tracks with p_T >100 MeV and p_T >500 MeV at √s=13 TeV for the minimum-bias (MB) and high-multiplicity track (HMT) events. The uncertainties represent the sum in quadrature of the statistical and systematic contributions. The curves represent the exponential fits to λ(k_T).

The k_T dependence of the source radius, R(k_T), obtained from the exponential fit to the R₂(Q) correlation functions for events with multiplicity n_ch ≥ 2 and transfer momentum of tracks with p_T >100 MeV and p_T >500 MeV at √s=13 TeV for the minimum-bias (MB) and high-multiplicity track (HMT) events. The uncertainties represent the sum in quadrature of the statistical and systematic contributions. The curves represent the exponential fits to R(k_T).

The k_T dependence of the source radius, R(k_T), obtained from the exponential fit to the R₂(Q) correlation functions for events with multiplicity n_ch ≥ 2 and transfer momentum of tracks with p_T >100 MeV and p_T >500 MeV at √s=13 TeV for the minimum-bias (MB) and high-multiplicity track (HMT) events. The uncertainties represent the sum in quadrature of the statistical and systematic contributions. The curves represent the exponential fits to R(k_T).

The k_T dependence of the source radius, R(k_T), obtained from the exponential fit to the R₂(Q) correlation functions for events with multiplicity n_ch ≥ 2 and transfer momentum of tracks with p_T >100 MeV and p_T >500 MeV at √s=13 TeV for the minimum-bias (MB) and high-multiplicity track (HMT) events. The uncertainties represent the sum in quadrature of the statistical and systematic contributions. The curves represent the exponential fits to R(k_T).

The k_T dependence of the source radius, R(k_T), obtained from the exponential fit to the R₂(Q) correlation functions for events with multiplicity n_ch ≥ 2 and transfer momentum of tracks with p_T >100 MeV and p_T >500 MeV at √s=13 TeV for the minimum-bias (MB) and high-multiplicity track (HMT) events. The uncertainties represent the sum in quadrature of the statistical and systematic contributions. The curves represent the exponential fits to R(k_T).

The two-dimensional dependence on m_ch and k_T for p_T > 100 MeV for the correlation strength, λ, obtained from the exponential fit to the R₂(Q) correlation functions using the MB sample for m_ch ≤ 3.08 and the HMT sample for m_ch > 3.08.

The two-dimensional dependence on m_ch and k_T for p_T > 100 MeV for the source radius, R, obtained from the exponential fit to the R₂(Q) correlation functions using the MB sample for m_ch ≤ 3.08 and the HMT sample for m_ch > 3.08.

The parameter λ for p_T > 100 MeV as a function of k_T in selected low m_ch intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.

The parameter λ for p_T > 100 MeV as a function of k_T in selected low m_ch intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.

The parameter λ for p_T > 100 MeV as a function of k_T in selected high m_ch intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.

The parameter λ for p_T > 100 MeV as a function of k_T in selected high m_ch intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.

The parameter λ for p_T > 100 MeV as a function of m_ch in k_T intervals between 0.1 and 0.5 GeV. The error bars and boxes represent the statistical and systematic contributions, respectively.

The parameter λ for p_T > 100 MeV as a function of m_ch in k_T intervals between 0.1 and 0.5 GeV. The error bars and boxes represent the statistical and systematic contributions, respectively.

The parameter λ for p_T > 100 MeV as a function of m_ch in k_T intervals between 0.5 and 1.5 GeV. The error bars and boxes represent the statistical and systematic contributions, respectively.

The parameter λ for p_T > 100 MeV as a function of m_ch in k_T intervals between 0.5 and 1.5 GeV. The error bars and boxes represent the statistical and systematic contributions, respectively.

The parameter R for p_T > 100 MeV as a function of k_T in selected low m_ch intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.

The parameter R for p_T > 100 MeV as a function of k_T in selected low m_ch intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.

The parameter R for p_T > 100 MeV as a function of k_T in selected high m_ch intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.

The parameter R for p_T > 100 MeV as a function of k_T in selected high m_ch intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.

The parameter R for p_T > 100 MeV as a function of m_ch in k_T intervals between 0.1 and 0.5 GeV. The error bars and boxes represent the statistical and systematic contributions, respectively.

The parameter R for p_T > 100 MeV as a function of m_ch in k_T intervals between 0.1 and 0.5 GeV. The error bars and boxes represent the statistical and systematic contributions, respectively.

The parameter R for p_T > 100 MeV as a function of m_ch in k_T intervals between 0.5 and 1.5 GeV. The error bars and boxes represent the statistical and systematic contributions, respectively.

The parameter R for p_T > 100 MeV as a function of m_ch in k_T intervals between 0.5 and 1.5 GeV. The error bars and boxes represent the statistical and systematic contributions, respectively.

The fit parameter μ describing the dependence of the correlation strength, λ, on charged-particle scaled multiplicity, for track p_T>100 MeV and track p_T>500 MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at √s = 13 TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid (blue dashed) curve represents the exponential fit of the dependence of parameter μ on m_ch for tracks with p_T >100 MeV (p_T >500 MeV).

The fit parameter μ describing the dependence of the correlation strength, λ, on charged-particle scaled multiplicity, for track p_T>100 MeV and track p_T>500 MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at √s = 13 TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid (blue dashed) curve represents the exponential fit of the dependence of parameter μ on m_ch for tracks with p_T >100 MeV (p_T >500 MeV).

The fit parameter μ describing the dependence of the correlation strength, λ, on charged-particle scaled multiplicity, for track p_T>100 MeV and track p_T>500 MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at √s = 13 TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid (blue dashed) curve represents the exponential fit of the dependence of parameter μ on m_ch for tracks with p_T >100 MeV (p_T >500 MeV).

The fit parameter μ describing the dependence of the correlation strength, λ, on charged-particle scaled multiplicity, for track p_T>100 MeV and track p_T>500 MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at √s = 13 TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid (blue dashed) curve represents the exponential fit of the dependence of parameter μ on m_ch for tracks with p_T >100 MeV (p_T >500 MeV).

The fit parameter ν describing the dependence of the correlation strength, λ, on charged-particle scaled multiplicity, for track p_T>100 MeV and track p_T>500 MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at √s = 13 TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid (blue dashed) curve represents the exponential fit of the dependence of parameter ν on m_ch for tracks with p_T >100 MeV (p_T >500 MeV).

The fit parameter ν describing the dependence of the correlation strength, λ, on charged-particle scaled multiplicity, for track p_T>100 MeV and track p_T>500 MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at √s = 13 TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid (blue dashed) curve represents the exponential fit of the dependence of parameter ν on m_ch for tracks with p_T >100 MeV (p_T >500 MeV).

The fit parameter ν describing the dependence of the correlation strength, λ, on charged-particle scaled multiplicity, for track p_T>100 MeV and track p_T>500 MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at √s = 13 TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid (blue dashed) curve represents the exponential fit of the dependence of parameter ν on m_ch for tracks with p_T >100 MeV (p_T >500 MeV).

The fit parameter ν describing the dependence of the correlation strength, λ, on charged-particle scaled multiplicity, for track p_T>100 MeV and track p_T>500 MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at √s = 13 TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid (blue dashed) curve represents the exponential fit of the dependence of parameter ν on m_ch for tracks with p_T >100 MeV (p_T >500 MeV).

The parameter ξ describing the dependence of the source radius, R, on charged-particle scaled multiplicity, m_ch, for track p_T>100 MeV and track p_T>500 MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at √s = 13 TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid and blue dashed curves represent the saturated value of the parameter ξ for m_ch > 3.0 for tracks with p_T >100 MeV and for m_ch > 2.8 for tracks with p_T >500 MeV, respectively.

The parameter ξ describing the dependence of the source radius, R, on charged-particle scaled multiplicity, m_ch, for track p_T>100 MeV and track p_T>500 MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at √s = 13 TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid and blue dashed curves represent the saturated value of the parameter ξ for m_ch > 3.0 for tracks with p_T >100 MeV and for m_ch > 2.8 for tracks with p_T >500 MeV, respectively.

The parameter ξ describing the dependence of the source radius, R, on charged-particle scaled multiplicity, m_ch, for track p_T>100 MeV and track p_T>500 MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at √s = 13 TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid and blue dashed curves represent the saturated value of the parameter ξ for m_ch > 3.0 for tracks with p_T >100 MeV and for m_ch > 2.8 for tracks with p_T >500 MeV, respectively.

The parameter ξ describing the dependence of the source radius, R, on charged-particle scaled multiplicity, m_ch, for track p_T>100 MeV and track p_T>500 MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at √s = 13 TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid and blue dashed curves represent the saturated value of the parameter ξ for m_ch > 3.0 for tracks with p_T >100 MeV and for m_ch > 2.8 for tracks with p_T >500 MeV, respectively.

The parameter κ describing the dependence of the source radius, R, on charged-particle scaled multiplicity, m_ch, for track p_T>100 MeV and track p_T>500 MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at √s = 13 TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid and blue dashed curves represent the exponential fit to the parameter κ for tracks with p_T >100 MeV and for tracks with p_T >500 MeV, respectively.

The parameter κ describing the dependence of the source radius, R, on charged-particle scaled multiplicity, m_ch, for track p_T>100 MeV and track p_T>500 MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at √s = 13 TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid and blue dashed curves represent the exponential fit to the parameter κ for tracks with p_T >100 MeV and for tracks with p_T >500 MeV, respectively.

The parameter κ describing the dependence of the source radius, R, on charged-particle scaled multiplicity, m_ch, for track p_T>100 MeV and track p_T>500 MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at √s = 13 TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid and blue dashed curves represent the exponential fit to the parameter κ for tracks with p_T >100 MeV and for tracks with p_T >500 MeV, respectively.

The parameter κ describing the dependence of the source radius, R, on charged-particle scaled multiplicity, m_ch, for track p_T>100 MeV and track p_T>500 MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at √s = 13 TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid and blue dashed curves represent the exponential fit to the parameter κ for tracks with p_T >100 MeV and for tracks with p_T >500 MeV, respectively.

The two-dimensional dependence on m_ch and k_T for p_T > 500 MeV for the correlation strength, λ, obtained from the exponential fit to the R₂(Q) correlation functions using the MB sample for m_ch ≤ 3.08 and the HMT sample for m_ch > 3.08.

The two-dimensional dependence on m_ch and k_T for p_T > 500 MeV for the source radius, R, obtained from the exponential fit to the R₂(Q) correlation functions using the MB sample for m_ch ≤ 3.08 and the HMT sample for m_ch > 3.08.

The parameter λ for p_T > 500 MeV as a function of k_T in selected low m_ch intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.

The parameter λ for p_T > 500 MeV as a function of k_T in selected low m_ch intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.

The parameter λ for p_T > 500 MeV as a function of k_T in selected high m_ch intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.

The parameter λ for p_T > 500 MeV as a function of k_T in selected high m_ch intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.

The parameter λ for p_T > 500 MeV as a function of m_ch in k_T intervals between 0.5 and 1.5 GeV. The error bars and boxes represent the statistical and systematic contributions, respectively.

The parameter λ for p_T > 500 MeV as a function of m_ch in k_T intervals between 0.5 and 1.5 GeV. The error bars and boxes represent the statistical and systematic contributions, respectively.

The parameter R for p_T > 500 MeV as a function of k_T in selected low m_ch intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.

The parameter R for p_T > 500 MeV as a function of k_T in selected low m_ch intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.

The parameter R for p_T > 500 MeV as a function of k_T in selected high m_ch intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.

The parameter R for p_T > 500 MeV as a function of k_T in selected high m_ch intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.

The parameter R for p_T > 500 MeV as a function of m_ch in k_T intervals between 0.5 and 1.5 GeV. The error bars and boxes represent the statistical and systematic contributions, respectively.

The parameter R for p_T > 500 MeV as a function of m_ch in k_T intervals between 0.5 and 1.5 GeV. The error bars and boxes represent the statistical and systematic contributions, respectively.

ATLAS and CMS results for the source radius R as a function of n_ch in pp interactions at 13 TeV. The CMS results (open circles) have been adjusted (by the CMS collaboration) to the ATLAS kinematic region∶ p_T > 100 MeV and |η|<2.5. The ATLAS uncertainties are the sum in quadrature of the statistical and asymmetric systematic uncertainties. For CMS, only the systematic uncertainties are shown since the statistical uncertainties are smaller than the marker size. The dashed blue (ATLAS) and black (CMS) lines represent the fit to ∛n_ch at low multiplicity, continued as dotted lines beyond the fit range. The solid green (ATLAS) and broken black (CMS) lines indicate the plateau level at high multiplicity.

ATLAS and CMS results for the source radius R as a function of n_ch in pp interactions at 13 TeV. The CMS results (open circles) have been adjusted (by the CMS collaboration) to the ATLAS kinematic region∶ p_T > 100 MeV and |η|<2.5. The ATLAS uncertainties are the sum in quadrature of the statistical and asymmetric systematic uncertainties. For CMS, only the systematic uncertainties are shown since the statistical uncertainties are smaller than the marker size. The dashed blue (ATLAS) and black (CMS) lines represent the fit to ∛n_ch at low multiplicity, continued as dotted lines beyond the fit range. The solid green (ATLAS) and broken black (CMS) lines indicate the plateau level at high multiplicity.

ATLAS and CMS results for the source radius R as a function of n_ch in pp interactions at 13 TeV. The CMS results (open circles) have been adjusted (by the CMS collaboration) to the ATLAS kinematic region∶ p_T > 100 MeV and |η|<2.5. The ATLAS uncertainties are the sum in quadrature of the statistical and asymmetric systematic uncertainties. For CMS, only the systematic uncertainties are shown since the statistical uncertainties are smaller than the marker size. The dashed blue (ATLAS) and black (CMS) lines represent the fit to ∛n_ch at low multiplicity, continued as dotted lines beyond the fit range. The solid green (ATLAS) and broken black (CMS) lines indicate the plateau level at high multiplicity.

ATLAS and CMS results for the source radius R as a function of ∛n_ch in pp interactions at 13 TeV. The CMS results (open circles) have been adjusted (by the CMS collaboration) to the ATLAS kinematic region∶ p_T > 100 MeV and |η|<2.5. The ATLAS uncertainties are the sum in quadrature of the statistical and asymmetric systematic uncertainties. For CMS, only the systematic uncertainties are shown since the statistical uncertainties are smaller than the marker size. The dashed blue (ATLAS) and black (CMS) lines represent the fit to ∛n_ch at low multiplicity, continued as dotted lines beyond the fit range. The solid green (ATLAS) and broken black (CMS) lines indicate the plateau level at high multiplicity.

ATLAS and CMS results for the source radius R as a function of ∛n_ch in pp interactions at 13 TeV. The CMS results (open circles) have been adjusted (by the CMS collaboration) to the ATLAS kinematic region∶ p_T > 100 MeV and |η|<2.5. The ATLAS uncertainties are the sum in quadrature of the statistical and asymmetric systematic uncertainties. For CMS, only the systematic uncertainties are shown since the statistical uncertainties are smaller than the marker size. The dashed blue (ATLAS) and black (CMS) lines represent the fit to ∛n_ch at low multiplicity, continued as dotted lines beyond the fit range. The solid green (ATLAS) and broken black (CMS) lines indicate the plateau level at high multiplicity.

ATLAS and CMS results for the source radius R as a function of ∛n_ch in pp interactions at 13 TeV. The CMS results (open circles) have been adjusted (by the CMS collaboration) to the ATLAS kinematic region∶ p_T > 100 MeV and |η|<2.5. The ATLAS uncertainties are the sum in quadrature of the statistical and asymmetric systematic uncertainties. For CMS, only the systematic uncertainties are shown since the statistical uncertainties are smaller than the marker size. The dashed blue (ATLAS) and black (CMS) lines represent the fit to ∛n_ch at low multiplicity, continued as dotted lines beyond the fit range. The solid green (ATLAS) and broken black (CMS) lines indicate the plateau level at high multiplicity.

Systematic uncertainties (in percent) in the correlation strength, λ, and source radius, R, for the exponential fit of the two-particle double-ratio correlation functions, R₂(Q), for p_T > 100 MeV at √s= 13 TeV for the MB and HMT events. The choice of MC generator gives rise to asymmetric uncertainties, denoted by uparrow and downarrow. This asymmetry propagates through to the cumulative uncertainty. The columns under ‘Uncertainty range’ show the range of systematic uncertainty from the fits in the various n_ch intervals.

The results of the fits to the dependencies of the correlation strength, λ, and source radius, R, on the average rescaled charged-particle multiplicity, m_ch, for |η| < 2.5 and both p_T > 100 MeV and p_T > 500 MeV at √s = 13 TeV for the minimum-bias (MB) and the high-multiplicity track (HMT) events. The parameters γ and δ resulting from a joint fit to the MB and HMT data are presented. The total uncertainties are shown.

The results of the fits to the dependencies of the correlation strength, λ, and source radius, R, on the pair average transverse momentum, k_T, for various functional forms and for minimum-bias (MB) and high-multiplicity track (HMT) events for p_T > 100 MeV and p_T > 500 MeV at √s = 13 TeV. The total uncertainties are shown.

The Bose-Einstein correlation (BEC) parameters λ and R as a function of n_ch and k_T using different MC generators in the calculation of R₂(Q). (a) λ versus n_ch for MB events, (b) λ versus n_ch for HMT events, (c) λ versus k_T and (d) R versus k_T for MB events. The uncertainties shown are statistical. The lower panel of each plot shows the ratio of the BEC parameters obtained using EPOS LHC (red circles), Pythia 8 Monash (blue squares) and Herwig++ UE-EE-5 (green triangles) compared with the parameters obtained using Pythia 8 A2. The gray band in the lower panels is the MC systematic uncertainty, obtained as explained in the text.

The Bose-Einstein correlation (BEC) parameters λ and R as a function of n_ch and k_T using different MC generators in the calculation of R₂(Q). (a) λ versus n_ch for MB events, (b) λ versus n_ch for HMT events, (c) λ versus k_T and (d) R versus k_T for MB events. The uncertainties shown are statistical. The lower panel of each plot shows the ratio of the BEC parameters obtained using EPOS LHC (red circles), Pythia 8 Monash (blue squares) and Herwig++ UE-EE-5 (green triangles) compared with the parameters obtained using Pythia 8 A2. The gray band in the lower panels is the MC systematic uncertainty, obtained as explained in the text.

The Bose-Einstein correlation (BEC) parameters λ and R as a function of n_ch and k_T using different MC generators in the calculation of R₂(Q). (a) λ versus n_ch for MB events, (b) λ versus n_ch for HMT events, (c) λ versus k_T and (d) R versus k_T for MB events. The uncertainties shown are statistical. The lower panel of each plot shows the ratio of the BEC parameters obtained using EPOS LHC (red circles), Pythia 8 Monash (blue squares) and Herwig++ UE-EE-5 (green triangles) compared with the parameters obtained using Pythia 8 A2. The gray band in the lower panels is the MC systematic uncertainty, obtained as explained in the text.

The Bose-Einstein correlation (BEC) parameters λ and R as a function of n_ch and k_T using different MC generators in the calculation of R₂(Q). (a) λ versus n_ch for MB events, (b) λ versus n_ch for HMT events, (c) λ versus k_T and (d) R versus k_T for MB events. The uncertainties shown are statistical. The lower panel of each plot shows the ratio of the BEC parameters obtained using EPOS LHC (red circles), Pythia 8 Monash (blue squares) and Herwig++ UE-EE-5 (green triangles) compared with the parameters obtained using Pythia 8 A2. The gray band in the lower panels is the MC systematic uncertainty, obtained as explained in the text.

The single-ratio two-particle correlation functions, C₂^data(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals∶ (a) 2 < n_ch ≤ 10, (b) 11 < n_ch ≤ 20, (c) 21 < n_ch ≤ 30, (d) 31 < n_ch ≤ 40, (e) 41 < n_ch ≤ 50, (f) 51 < n_ch ≤ 60, (g) 61 < n_ch ≤ 70, (h) 71 < n_ch ≤ 80 and (i) 81 < n_ch ≤ 90. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals∶ (a) 2 < n_ch ≤ 10, (b) 11 < n_ch ≤ 20, (c) 21 < n_ch ≤ 30, (d) 31 < n_ch ≤ 40, (e) 41 < n_ch ≤ 50, (f) 51 < n_ch ≤ 60, (g) 61 < n_ch ≤ 70, (h) 71 < n_ch ≤ 80 and (i) 81 < n_ch ≤ 90. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals∶ (a) 2 < n_ch ≤ 10, (b) 11 < n_ch ≤ 20, (c) 21 < n_ch ≤ 30, (d) 31 < n_ch ≤ 40, (e) 41 < n_ch ≤ 50, (f) 51 < n_ch ≤ 60, (g) 61 < n_ch ≤ 70, (h) 71 < n_ch ≤ 80 and (i) 81 < n_ch ≤ 90. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals∶ (a) 2 < n_ch ≤ 10, (b) 11 < n_ch ≤ 20, (c) 21 < n_ch ≤ 30, (d) 31 < n_ch ≤ 40, (e) 41 < n_ch ≤ 50, (f) 51 < n_ch ≤ 60, (g) 61 < n_ch ≤ 70, (h) 71 < n_ch ≤ 80 and (i) 81 < n_ch ≤ 90. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals∶ (a) 2 < n_ch ≤ 10, (b) 11 < n_ch ≤ 20, (c) 21 < n_ch ≤ 30, (d) 31 < n_ch ≤ 40, (e) 41 < n_ch ≤ 50, (f) 51 < n_ch ≤ 60, (g) 61 < n_ch ≤ 70, (h) 71 < n_ch ≤ 80 and (i) 81 < n_ch ≤ 90. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals∶ (a) 2 < n_ch ≤ 10, (b) 11 < n_ch ≤ 20, (c) 21 < n_ch ≤ 30, (d) 31 < n_ch ≤ 40, (e) 41 < n_ch ≤ 50, (f) 51 < n_ch ≤ 60, (g) 61 < n_ch ≤ 70, (h) 71 < n_ch ≤ 80 and (i) 81 < n_ch ≤ 90. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals∶ (a) 2 < n_ch ≤ 10, (b) 11 < n_ch ≤ 20, (c) 21 < n_ch ≤ 30, (d) 31 < n_ch ≤ 40, (e) 41 < n_ch ≤ 50, (f) 51 < n_ch ≤ 60, (g) 61 < n_ch ≤ 70, (h) 71 < n_ch ≤ 80 and (i) 81 < n_ch ≤ 90. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals∶ (a) 2 < n_ch ≤ 10, (b) 11 < n_ch ≤ 20, (c) 21 < n_ch ≤ 30, (d) 31 < n_ch ≤ 40, (e) 41 < n_ch ≤ 50, (f) 51 < n_ch ≤ 60, (g) 61 < n_ch ≤ 70, (h) 71 < n_ch ≤ 80 and (i) 81 < n_ch ≤ 90. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals∶ (a) 2 < n_ch ≤ 10, (b) 11 < n_ch ≤ 20, (c) 21 < n_ch ≤ 30, (d) 31 < n_ch ≤ 40, (e) 41 < n_ch ≤ 50, (f) 51 < n_ch ≤ 60, (g) 61 < n_ch ≤ 70, (h) 71 < n_ch ≤ 80 and (i) 81 < n_ch ≤ 90. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals∶ (a) 91 < n_ch ≤ 100, (b) 101 < n_ch ≤ 125, (c) 126 < n_ch ≤ 150, (d) 151 < n_ch ≤ 200, (e) 201 < n_ch ≤ 250. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals∶ (a) 91 < n_ch ≤ 100, (b) 101 < n_ch ≤ 125, (c) 126 < n_ch ≤ 150, (d) 151 < n_ch ≤ 200, (e) 201 < n_ch ≤ 250. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals∶ (a) 91 < n_ch ≤ 100, (b) 101 < n_ch ≤ 125, (c) 126 < n_ch ≤ 150, (d) 151 < n_ch ≤ 200, (e) 201 < n_ch ≤ 250. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals∶ (a) 91 < n_ch ≤ 100, (b) 101 < n_ch ≤ 125, (c) 126 < n_ch ≤ 150, (d) 151 < n_ch ≤ 200, (e) 201 < n_ch ≤ 250. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals∶ (a) 91 < n_ch ≤ 100, (b) 101 < n_ch ≤ 125, (c) 126 < n_ch ≤ 150, (d) 151 < n_ch ≤ 200, (e) 201 < n_ch ≤ 250. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals∶ (a) 101 < n_ch ≤ 110, (b) 111 < n_ch ≤ 120, (c) 121 < n_ch ≤ 130, (d) 131 < n_ch ≤ 140, (e) 141 < n_ch ≤ 155, (f) 156 < n_ch ≤ 175, (g) 176 < n_ch ≤ 200, (h) 201 < n_ch ≤ 230 and (i) 231 < n_ch ≤ 300. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals∶ (a) 101 < n_ch ≤ 110, (b) 111 < n_ch ≤ 120, (c) 121 < n_ch ≤ 130, (d) 131 < n_ch ≤ 140, (e) 141 < n_ch ≤ 155, (f) 156 < n_ch ≤ 175, (g) 176 < n_ch ≤ 200, (h) 201 < n_ch ≤ 230 and (i) 231 < n_ch ≤ 300. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals∶ (a) 101 < n_ch ≤ 110, (b) 111 < n_ch ≤ 120, (c) 121 < n_ch ≤ 130, (d) 131 < n_ch ≤ 140, (e) 141 < n_ch ≤ 155, (f) 156 < n_ch ≤ 175, (g) 176 < n_ch ≤ 200, (h) 201 < n_ch ≤ 230 and (i) 231 < n_ch ≤ 300. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals∶ (a) 101 < n_ch ≤ 110, (b) 111 < n_ch ≤ 120, (c) 121 < n_ch ≤ 130, (d) 131 < n_ch ≤ 140, (e) 141 < n_ch ≤ 155, (f) 156 < n_ch ≤ 175, (g) 176 < n_ch ≤ 200, (h) 201 < n_ch ≤ 230 and (i) 231 < n_ch ≤ 300. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals∶ (a) 101 < n_ch ≤ 110, (b) 111 < n_ch ≤ 120, (c) 121 < n_ch ≤ 130, (d) 131 < n_ch ≤ 140, (e) 141 < n_ch ≤ 155, (f) 156 < n_ch ≤ 175, (g) 176 < n_ch ≤ 200, (h) 201 < n_ch ≤ 230 and (i) 231 < n_ch ≤ 300. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals∶ (a) 101 < n_ch ≤ 110, (b) 111 < n_ch ≤ 120, (c) 121 < n_ch ≤ 130, (d) 131 < n_ch ≤ 140, (e) 141 < n_ch ≤ 155, (f) 156 < n_ch ≤ 175, (g) 176 < n_ch ≤ 200, (h) 201 < n_ch ≤ 230 and (i) 231 < n_ch ≤ 300. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals∶ (a) 101 < n_ch ≤ 110, (b) 111 < n_ch ≤ 120, (c) 121 < n_ch ≤ 130, (d) 131 < n_ch ≤ 140, (e) 141 < n_ch ≤ 155, (f) 156 < n_ch ≤ 175, (g) 176 < n_ch ≤ 200, (h) 201 < n_ch ≤ 230 and (i) 231 < n_ch ≤ 300. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals∶ (a) 101 < n_ch ≤ 110, (b) 111 < n_ch ≤ 120, (c) 121 < n_ch ≤ 130, (d) 131 < n_ch ≤ 140, (e) 141 < n_ch ≤ 155, (f) 156 < n_ch ≤ 175, (g) 176 < n_ch ≤ 200, (h) 201 < n_ch ≤ 230 and (i) 231 < n_ch ≤ 300. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals∶ (a) 101 < n_ch ≤ 110, (b) 111 < n_ch ≤ 120, (c) 121 < n_ch ≤ 130, (d) 131 < n_ch ≤ 140, (e) 141 < n_ch ≤ 155, (f) 156 < n_ch ≤ 175, (g) 176 < n_ch ≤ 200, (h) 201 < n_ch ≤ 230 and (i) 231 < n_ch ≤ 300. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k_T - intervals∶ (a) 100 < k_T ≤ 200 MeV, (b) 200 < k_T ≤ 300 MeV, (c) 300 < k_T ≤ 400 MeV, (d) 400 < k_T ≤ 500 MeV, (e) 500 < k_T ≤ 600 MeV, (f) 600 < k_T ≤ 700 MeV, (g) 700 < k_T ≤ 1000 MeV, and (h) 1000 < k_T ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k_T - intervals∶ (a) 100 < k_T ≤ 200 MeV, (b) 200 < k_T ≤ 300 MeV, (c) 300 < k_T ≤ 400 MeV, (d) 400 < k_T ≤ 500 MeV, (e) 500 < k_T ≤ 600 MeV, (f) 600 < k_T ≤ 700 MeV, (g) 700 < k_T ≤ 1000 MeV, and (h) 1000 < k_T ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k_T - intervals∶ (a) 100 < k_T ≤ 200 MeV, (b) 200 < k_T ≤ 300 MeV, (c) 300 < k_T ≤ 400 MeV, (d) 400 < k_T ≤ 500 MeV, (e) 500 < k_T ≤ 600 MeV, (f) 600 < k_T ≤ 700 MeV, (g) 700 < k_T ≤ 1000 MeV, and (h) 1000 < k_T ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k_T - intervals∶ (a) 100 < k_T ≤ 200 MeV, (b) 200 < k_T ≤ 300 MeV, (c) 300 < k_T ≤ 400 MeV, (d) 400 < k_T ≤ 500 MeV, (e) 500 < k_T ≤ 600 MeV, (f) 600 < k_T ≤ 700 MeV, (g) 700 < k_T ≤ 1000 MeV, and (h) 1000 < k_T ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k_T - intervals∶ (a) 100 < k_T ≤ 200 MeV, (b) 200 < k_T ≤ 300 MeV, (c) 300 < k_T ≤ 400 MeV, (d) 400 < k_T ≤ 500 MeV, (e) 500 < k_T ≤ 600 MeV, (f) 600 < k_T ≤ 700 MeV, (g) 700 < k_T ≤ 1000 MeV, and (h) 1000 < k_T ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k_T - intervals∶ (a) 100 < k_T ≤ 200 MeV, (b) 200 < k_T ≤ 300 MeV, (c) 300 < k_T ≤ 400 MeV, (d) 400 < k_T ≤ 500 MeV, (e) 500 < k_T ≤ 600 MeV, (f) 600 < k_T ≤ 700 MeV, (g) 700 < k_T ≤ 1000 MeV, and (h) 1000 < k_T ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k_T - intervals∶ (a) 100 < k_T ≤ 200 MeV, (b) 200 < k_T ≤ 300 MeV, (c) 300 < k_T ≤ 400 MeV, (d) 400 < k_T ≤ 500 MeV, (e) 500 < k_T ≤ 600 MeV, (f) 600 < k_T ≤ 700 MeV, (g) 700 < k_T ≤ 1000 MeV, and (h) 1000 < k_T ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k_T - intervals∶ (a) 100 < k_T ≤ 200 MeV, (b) 200 < k_T ≤ 300 MeV, (c) 300 < k_T ≤ 400 MeV, (d) 400 < k_T ≤ 500 MeV, (e) 500 < k_T ≤ 600 MeV, (f) 600 < k_T ≤ 700 MeV, (g) 700 < k_T ≤ 1000 MeV, and (h) 1000 < k_T ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for k_T - intervals∶ (a) 100 < k_T ≤ 200 MeV, (b) 200 < k_T ≤ 300 MeV, (c) 300 < k_T ≤ 400 MeV, (d) 400 < k_T ≤ 500 MeV, (e) 500 < k_T ≤ 600 MeV, (f) 600 < k_T ≤ 700 MeV, (g) 700 < k_T ≤ 1000 MeV, and (h) 1000 < k_T ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for k_T - intervals∶ (a) 100 < k_T ≤ 200 MeV, (b) 200 < k_T ≤ 300 MeV, (c) 300 < k_T ≤ 400 MeV, (d) 400 < k_T ≤ 500 MeV, (e) 500 < k_T ≤ 600 MeV, (f) 600 < k_T ≤ 700 MeV, (g) 700 < k_T ≤ 1000 MeV, and (h) 1000 < k_T ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for k_T - intervals∶ (a) 100 < k_T ≤ 200 MeV, (b) 200 < k_T ≤ 300 MeV, (c) 300 < k_T ≤ 400 MeV, (d) 400 < k_T ≤ 500 MeV, (e) 500 < k_T ≤ 600 MeV, (f) 600 < k_T ≤ 700 MeV, (g) 700 < k_T ≤ 1000 MeV, and (h) 1000 < k_T ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for k_T - intervals∶ (a) 100 < k_T ≤ 200 MeV, (b) 200 < k_T ≤ 300 MeV, (c) 300 < k_T ≤ 400 MeV, (d) 400 < k_T ≤ 500 MeV, (e) 500 < k_T ≤ 600 MeV, (f) 600 < k_T ≤ 700 MeV, (g) 700 < k_T ≤ 1000 MeV, and (h) 1000 < k_T ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for k_T - intervals∶ (a) 100 < k_T ≤ 200 MeV, (b) 200 < k_T ≤ 300 MeV, (c) 300 < k_T ≤ 400 MeV, (d) 400 < k_T ≤ 500 MeV, (e) 500 < k_T ≤ 600 MeV, (f) 600 < k_T ≤ 700 MeV, (g) 700 < k_T ≤ 1000 MeV, and (h) 1000 < k_T ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for k_T - intervals∶ (a) 100 < k_T ≤ 200 MeV, (b) 200 < k_T ≤ 300 MeV, (c) 300 < k_T ≤ 400 MeV, (d) 400 < k_T ≤ 500 MeV, (e) 500 < k_T ≤ 600 MeV, (f) 600 < k_T ≤ 700 MeV, (g) 700 < k_T ≤ 1000 MeV, and (h) 1000 < k_T ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for k_T - intervals∶ (a) 100 < k_T ≤ 200 MeV, (b) 200 < k_T ≤ 300 MeV, (c) 300 < k_T ≤ 400 MeV, (d) 400 < k_T ≤ 500 MeV, (e) 500 < k_T ≤ 600 MeV, (f) 600 < k_T ≤ 700 MeV, (g) 700 < k_T ≤ 1000 MeV, and (h) 1000 < k_T ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for k_T - intervals∶ (a) 100 < k_T ≤ 200 MeV, (b) 200 < k_T ≤ 300 MeV, (c) 300 < k_T ≤ 400 MeV, (d) 400 < k_T ≤ 500 MeV, (e) 500 < k_T ≤ 600 MeV, (f) 600 < k_T ≤ 700 MeV, (g) 700 < k_T ≤ 1000 MeV, and (h) 1000 < k_T ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals∶ (a) 2 < n_ch ≤ 9, (b) 10 < n_ch ≤ 18, (c) 19 < n_ch ≤ 27, (d) 28 < n_ch ≤ 36, (e) 37 < n_ch ≤ 45, (f) 46 < n_ch ≤ 54, (g) 55 < n_ch ≤ 63, (h) 64 < n_ch ≤ 72, (i) 73 < n_ch ≤ 81, (j) 82 < n_ch ≤ 90, (k) 91 < n_ch ≤ 113, and (l) 114 < n_ch ≤ 136. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals∶ (a) 2 < n_ch ≤ 9, (b) 10 < n_ch ≤ 18, (c) 19 < n_ch ≤ 27, (d) 28 < n_ch ≤ 36, (e) 37 < n_ch ≤ 45, (f) 46 < n_ch ≤ 54, (g) 55 < n_ch ≤ 63, (h) 64 < n_ch ≤ 72, (i) 73 < n_ch ≤ 81, (j) 82 < n_ch ≤ 90, (k) 91 < n_ch ≤ 113, and (l) 114 < n_ch ≤ 136. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals∶ (a) 2 < n_ch ≤ 9, (b) 10 < n_ch ≤ 18, (c) 19 < n_ch ≤ 27, (d) 28 < n_ch ≤ 36, (e) 37 < n_ch ≤ 45, (f) 46 < n_ch ≤ 54, (g) 55 < n_ch ≤ 63, (h) 64 < n_ch ≤ 72, (i) 73 < n_ch ≤ 81, (j) 82 < n_ch ≤ 90, (k) 91 < n_ch ≤ 113, and (l) 114 < n_ch ≤ 136. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals∶ (a) 2 < n_ch ≤ 9, (b) 10 < n_ch ≤ 18, (c) 19 < n_ch ≤ 27, (d) 28 < n_ch ≤ 36, (e) 37 < n_ch ≤ 45, (f) 46 < n_ch ≤ 54, (g) 55 < n_ch ≤ 63, (h) 64 < n_ch ≤ 72, (i) 73 < n_ch ≤ 81, (j) 82 < n_ch ≤ 90, (k) 91 < n_ch ≤ 113, and (l) 114 < n_ch ≤ 136. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals∶ (a) 2 < n_ch ≤ 9, (b) 10 < n_ch ≤ 18, (c) 19 < n_ch ≤ 27, (d) 28 < n_ch ≤ 36, (e) 37 < n_ch ≤ 45, (f) 46 < n_ch ≤ 54, (g) 55 < n_ch ≤ 63, (h) 64 < n_ch ≤ 72, (i) 73 < n_ch ≤ 81, (j) 82 < n_ch ≤ 90, (k) 91 < n_ch ≤ 113, and (l) 114 < n_ch ≤ 136. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals∶ (a) 2 < n_ch ≤ 9, (b) 10 < n_ch ≤ 18, (c) 19 < n_ch ≤ 27, (d) 28 < n_ch ≤ 36, (e) 37 < n_ch ≤ 45, (f) 46 < n_ch ≤ 54, (g) 55 < n_ch ≤ 63, (h) 64 < n_ch ≤ 72, (i) 73 < n_ch ≤ 81, (j) 82 < n_ch ≤ 90, (k) 91 < n_ch ≤ 113, and (l) 114 < n_ch ≤ 136. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals∶ (a) 2 < n_ch ≤ 9, (b) 10 < n_ch ≤ 18, (c) 19 < n_ch ≤ 27, (d) 28 < n_ch ≤ 36, (e) 37 < n_ch ≤ 45, (f) 46 < n_ch ≤ 54, (g) 55 < n_ch ≤ 63, (h) 64 < n_ch ≤ 72, (i) 73 < n_ch ≤ 81, (j) 82 < n_ch ≤ 90, (k) 91 < n_ch ≤ 113, and (l) 114 < n_ch ≤ 136. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals∶ (a) 2 < n_ch ≤ 9, (b) 10 < n_ch ≤ 18, (c) 19 < n_ch ≤ 27, (d) 28 < n_ch ≤ 36, (e) 37 < n_ch ≤ 45, (f) 46 < n_ch ≤ 54, (g) 55 < n_ch ≤ 63, (h) 64 < n_ch ≤ 72, (i) 73 < n_ch ≤ 81, (j) 82 < n_ch ≤ 90, (k) 91 < n_ch ≤ 113, and (l) 114 < n_ch ≤ 136. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals∶ (a) 2 < n_ch ≤ 9, (b) 10 < n_ch ≤ 18, (c) 19 < n_ch ≤ 27, (d) 28 < n_ch ≤ 36, (e) 37 < n_ch ≤ 45, (f) 46 < n_ch ≤ 54, (g) 55 < n_ch ≤ 63, (h) 64 < n_ch ≤ 72, (i) 73 < n_ch ≤ 81, (j) 82 < n_ch ≤ 90, (k) 91 < n_ch ≤ 113, and (l) 114 < n_ch ≤ 136. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals∶ (a) 2 < n_ch ≤ 9, (b) 10 < n_ch ≤ 18, (c) 19 < n_ch ≤ 27, (d) 28 < n_ch ≤ 36, (e) 37 < n_ch ≤ 45, (f) 46 < n_ch ≤ 54, (g) 55 < n_ch ≤ 63, (h) 64 < n_ch ≤ 72, (i) 73 < n_ch ≤ 81, (j) 82 < n_ch ≤ 90, (k) 91 < n_ch ≤ 113, and (l) 114 < n_ch ≤ 136. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals∶ (a) 2 < n_ch ≤ 9, (b) 10 < n_ch ≤ 18, (c) 19 < n_ch ≤ 27, (d) 28 < n_ch ≤ 36, (e) 37 < n_ch ≤ 45, (f) 46 < n_ch ≤ 54, (g) 55 < n_ch ≤ 63, (h) 64 < n_ch ≤ 72, (i) 73 < n_ch ≤ 81, (j) 82 < n_ch ≤ 90, (k) 91 < n_ch ≤ 113, and (l) 114 < n_ch ≤ 136. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals∶ (a) 2 < n_ch ≤ 9, (b) 10 < n_ch ≤ 18, (c) 19 < n_ch ≤ 27, (d) 28 < n_ch ≤ 36, (e) 37 < n_ch ≤ 45, (f) 46 < n_ch ≤ 54, (g) 55 < n_ch ≤ 63, (h) 64 < n_ch ≤ 72, (i) 73 < n_ch ≤ 81, (j) 82 < n_ch ≤ 90, (k) 91 < n_ch ≤ 113, and (l) 114 < n_ch ≤ 136. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k_T - intervals∶ (a) 100 < k_T ≤ 200 MeV, (b) 200 < k_T ≤ 300 MeV, (c) 300 < k_T ≤ 400 MeV, (d) 400 < k_T ≤ 500 MeV, (e) 500 < k_T ≤ 600 MeV, (f) 600 < k_T ≤ 700 MeV, (g) 700 < k_T ≤ 1000 MeV, and (h) 1000 < k_T ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k_T - intervals∶ (a) 100 < k_T ≤ 200 MeV, (b) 200 < k_T ≤ 300 MeV, (c) 300 < k_T ≤ 400 MeV, (d) 400 < k_T ≤ 500 MeV, (e) 500 < k_T ≤ 600 MeV, (f) 600 < k_T ≤ 700 MeV, (g) 700 < k_T ≤ 1000 MeV, and (h) 1000 < k_T ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k_T - intervals∶ (a) 100 < k_T ≤ 200 MeV, (b) 200 < k_T ≤ 300 MeV, (c) 300 < k_T ≤ 400 MeV, (d) 400 < k_T ≤ 500 MeV, (e) 500 < k_T ≤ 600 MeV, (f) 600 < k_T ≤ 700 MeV, (g) 700 < k_T ≤ 1000 MeV, and (h) 1000 < k_T ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k_T - intervals∶ (a) 100 < k_T ≤ 200 MeV, (b) 200 < k_T ≤ 300 MeV, (c) 300 < k_T ≤ 400 MeV, (d) 400 < k_T ≤ 500 MeV, (e) 500 < k_T ≤ 600 MeV, (f) 600 < k_T ≤ 700 MeV, (g) 700 < k_T ≤ 1000 MeV, and (h) 1000 < k_T ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k_T - intervals∶ (a) 100 < k_T ≤ 200 MeV, (b) 200 < k_T ≤ 300 MeV, (c) 300 < k_T ≤ 400 MeV, (d) 400 < k_T ≤ 500 MeV, (e) 500 < k_T ≤ 600 MeV, (f) 600 < k_T ≤ 700 MeV, (g) 700 < k_T ≤ 1000 MeV, and (h) 1000 < k_T ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k_T - intervals∶ (a) 100 < k_T ≤ 200 MeV, (b) 200 < k_T ≤ 300 MeV, (c) 300 < k_T ≤ 400 MeV, (d) 400 < k_T ≤ 500 MeV, (e) 500 < k_T ≤ 600 MeV, (f) 600 < k_T ≤ 700 MeV, (g) 700 < k_T ≤ 1000 MeV, and (h) 1000 < k_T ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k_T - intervals∶ (a) 100 < k_T ≤ 200 MeV, (b) 200 < k_T ≤ 300 MeV, (c) 300 < k_T ≤ 400 MeV, (d) 400 < k_T ≤ 500 MeV, (e) 500 < k_T ≤ 600 MeV, (f) 600 < k_T ≤ 700 MeV, (g) 700 < k_T ≤ 1000 MeV, and (h) 1000 < k_T ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k_T - intervals∶ (a) 100 < k_T ≤ 200 MeV, (b) 200 < k_T ≤ 300 MeV, (c) 300 < k_T ≤ 400 MeV, (d) 400 < k_T ≤ 500 MeV, (e) 500 < k_T ≤ 600 MeV, (f) 600 < k_T ≤ 700 MeV, (g) 700 < k_T ≤ 1000 MeV, and (h) 1000 < k_T ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The correlation strength, λ, and source radius, R, of the exponential fits to the two-particle double-ratio correlation functions, R₂(Q), in dependence on the multiplicity, m_ch, intervals for the minimum-bias (MB) and the high-multiplicity track (HMT) events for p_T > 100 MeV at √s = 13 TeV. Statistical uncertainties for √χ²/ndf>1 are corrected by the √χ²/ndf. The total uncertainties are shown.

The correlation strength, λ, and source radius, R, of the exponential fits to the two-particle double-ratio correlation functions, R₂(Q), in dependence on the multiplicity, m_ch, intervals for the minimum-bias (MB) and the high-multiplicity track (HMT) events for p_T > 500 MeV at √s = 13 TeV. Statistical uncertainties for √χ²/ndf>1 are corrected by the √χ²/ndf. The total uncertainties are shown.

The correlation strength, λ, and source radius, R, of the exponential fits to the two-particle double-ratio correlation functions, R₂(Q), in dependence on the pair transverse momentum, k_T, intervals for the minimum-bias (MB) and the high-multiplicity track (HMT) events for p_T > 100 MeV at √s = 13 TeV. Statistical uncertainties for √χ²/ndf>1 are corrected by the √χ²/ndf. The total uncertainties are shown.

The correlation strength, λ, and source radius, R, of the exponential fits to the two-particle double-ratio correlation functions, R₂(Q), in dependence on the pair transverse momentum, k_T, intervals for the minimum-bias (MB) and the high-multiplicity track (HMT) events for p_T > 500 MeV at √s = 13 TeV. Statistical uncertainties for √χ²/ndf>1 are corrected by the √χ²/ndf. The total uncertainties are shown.

Measured differential cross section with associated uncertainties as a function of $N$($b$-jets). Each systematic uncertainty source is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate. For the meaning of the bins please refer to the figure.

Measured differential cross section with associated uncertainties as a function of $p_{T}^{j1}$. Each systematic uncertainty source is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of $p_{T}^{\gamma\gamma} (N_\mathrm{jets}^{p_T>30\ \mathrm{GeV}}=0)$. Each systematic uncertainty source is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of $m_{jj}$. Each systematic uncertainty source is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of $\Delta\phi_{jj}$. Each systematic uncertainty source is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of $p_{T}^{\gamma\gamma}$ in bins of $|y_{\gamma\gamma}|$. Each systematic uncertainty source is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of $\Delta\phi_{jj}$ in the VBF fiducial region. Each systematic uncertainty source is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Observed statistical correlations, evaluated with a bootstrapping technique, between $p_\mathrm{T}^{\gamma\gamma}$, $N_\mathrm{jets}$, $m_{jj}$, $\Delta\phi_{jj}$, and $p_\mathrm{T}^{j1}$

Post-fit correlation matrix for the differential cross section measured as a function of $p_{T}^{\gamma\gamma}$.

Post-fit correlation matrix for the differential cross section measured as a function of $N_\mathrm{jets}$.

Post-fit correlation matrix for the differential cross section measured as a function of $N$($b$-jets).

Post-fit correlation matrix for the differential cross section measured as a function of $p_{T}^{j1}$.

Post-fit correlation matrix for the differential cross section measured as a function of $p_{T}^{\gamma\gamma} (N_\mathrm{jets}^{p_T>30\ \mathrm{GeV}}=0)$.

Post-fit correlation matrix for the differential cross section measured as a function of $m_{jj}$.

Post-fit correlation matrix for the differential cross section measured as a function of $\Delta\phi_{jj}$.

Post-fit correlation matrix for the differential cross section measured as a function of $\Delta\phi_{jj}$ in the VBF fiducial region.

Post-fit correlation matrix for the differential cross section measured as a function of $p_{T}^{\gamma\gamma}$ in bins of $|y_{\gamma\gamma}|$. The bins are the same as in the corresponding plot of the differential cross section.

Measured differential cross section with associated uncertainties as a function of $p_{T}^{\gamma1}/m_{\gamma\gamma}$. Each systematic uncertainty source is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Post-fit correlation matrix for the differential cross section measured as a function of $p_{T}^{\gamma1}/m_{\gamma\gamma}$.

Measured differential cross section with associated uncertainties as a function of $p_{T}^{\gamma2}/m_{\gamma\gamma}$. Each systematic uncertainty source is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Post-fit correlation matrix for the differential cross section measured as a function of $p_{T}^{\gamma2}/m_{\gamma\gamma}$.

Measured differential cross section with associated uncertainties as a function of $|y_{\gamma\gamma}|$. Each systematic uncertainty source is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Post-fit correlation matrix for the differential cross section measured as a function of $|y_{\gamma\gamma}|$.

Measured differential cross section with associated uncertainties as a function of $m_{\gamma\gamma j}$. Each systematic uncertainty source is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Post-fit correlation matrix for the differential cross section measured as a function of $m_{\gamma\gamma j}$.

Measured differential cross section with associated uncertainties as a function of $p_{T}^{\gamma\gamma j}$. Each systematic uncertainty source is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Post-fit correlation matrix for the differential cross section measured as a function of $p_{T}^{\gamma\gamma j}$.

Measured differential cross section with associated uncertainties as a function of $H_{T}$. Each systematic uncertainty source is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Post-fit correlation matrix for the differential cross section measured as a function of $H_{T}$.

Measured differential cross section with associated uncertainties as a function of $\tau_{C,j1}$. Each systematic uncertainty source is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Post-fit correlation matrix for the differential cross section measured as a function of $\tau_{C,j1}$.

Measured differential cross section with associated uncertainties as a function of $\sum\tau_{C,j}$. Each systematic uncertainty source is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Post-fit correlation matrix for the differential cross section measured as a function of $\sum\tau_{C,j}$.

Measured differential cross section with associated uncertainties as a function of $p_{T}^{\gamma\gamma} (N_\mathrm{jets}^{p_T>40\ \mathrm{GeV}}=0)$. Each systematic uncertainty source is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Post-fit correlation matrix for the differential cross section measured as a function of $p_{T}^{\gamma\gamma} (N_\mathrm{jets}^{p_T>40\ \mathrm{GeV}}=0)$.

Measured differential cross section with associated uncertainties as a function of $p_{T}^{\gamma\gamma} (N_\mathrm{jets}^{p_T>50\ \mathrm{GeV}}=0)$. Each systematic uncertainty source is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Post-fit correlation matrix for the differential cross section measured as a function of $p_{T}^{\gamma\gamma} (N_\mathrm{jets}^{p_T>50\ \mathrm{GeV}}=0)$.

Measured differential cross section with associated uncertainties as a function of $p_{T}^{\gamma\gamma} (N_\mathrm{jets}^{p_T>60\ \mathrm{GeV}}=0)$. Each systematic uncertainty source is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Post-fit correlation matrix for the differential cross section measured as a function of $p_{T}^{\gamma\gamma} (N_\mathrm{jets}^{p_T>60\ \mathrm{GeV}}=0)$.

Measured differential cross section with associated uncertainties as a function of $\pi - |\Delta\phi_{\gamma\gamma,jj}|$. Each systematic uncertainty source is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Post-fit correlation matrix for the differential cross section measured as a function of $\pi - |\Delta\phi_{\gamma\gamma,jj}|$.

Measured differential cross section with associated uncertainties as a function of $p_{T}^{\gamma\gamma jj}$. Each systematic uncertainty source is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Post-fit correlation matrix for the differential cross section measured as a function of $p_{T}^{\gamma\gamma jj}$.

Measured differential cross section with associated uncertainties as a function of $p_{T}^{\gamma\gamma}$ in bins of $p_{T}^{\gamma\gamma j}$. Each systematic uncertainty source is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Post-fit correlation matrix for the differential cross section measured as a function of $p_{T}^{\gamma\gamma}$ in bins of $p_{T}^{\gamma\gamma j}$. The bins are the same as in the corresponding plot of the differential cross section.

Measured differential cross section with associated uncertainties as a function of $p_{T}^{\gamma\gamma}$ in bins of $\tau_{C,j1}$. Each systematic uncertainty source is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Post-fit correlation matrix for the differential cross section measured as a function of $p_{T}^{\gamma\gamma}$ in bins of $\tau_{C,j1}$. The bins are the same as in the corresponding plot of the differential cross section.

Measured differential cross section with associated uncertainties as a function of $(p_{T}^{\gamma1}-p_{T}^{\gamma2})/m_{\gamma\gamma}$ in bins of $(p_{T}^{\gamma1}+p_{T}^{\gamma2})/m_{\gamma\gamma}$. Each systematic uncertainty source is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Post-fit correlation matrix for the differential cross section measured as a function of $(p_{T}^{\gamma1}-p_{T}^{\gamma2})/m_{\gamma\gamma}$ in bins of $(p_{T}^{\gamma1}+p_{T}^{\gamma2})/m_{\gamma\gamma}$. The bins are the same as in the corresponding plot of the differential cross section.

Measured differential cross section with associated uncertainties as a function of $|\eta^*|$ in the VBF fiducial region. Each systematic uncertainty source is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Post-fit correlation matrix for the differential cross section measured as a function of $|\eta^*|$ in the VBF fiducial region.

Measured differential cross section with associated uncertainties as a function of $p_{T}^{\gamma\gamma jj}$ in the VBF fiducial region. Each systematic uncertainty source is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Post-fit correlation matrix for the differential cross section measured as a function of $p_{T}^{\gamma\gamma jj}$ in the VBF fiducial region.

Measured differential cross section with associated uncertainties as a function of $p_{T}^{j1}$ in the VBF fiducial region. Each systematic uncertainty source is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Post-fit correlation matrix for the differential cross section measured as a function of $p_{T}^{j1}$ in the VBF fiducial region.

Measured differential cross section with associated uncertainties as a function of $p_{T}^{j1}$ in bins of $\Delta\phi_{jj}$ in the VBF fiducial region. Each systematic uncertainty source is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Post-fit correlation matrix for the differential cross section measured as a function of $p_{T}^{j1}$ in bins of $\Delta\phi_{jj}$ in the VBF fiducial region. The bins are the same as in the corresponding plot of the differential cross section.

Observed yields in the boost_0_ge2J signal region category of the hh channel.

Observed yields in the boost_1_1J signal region category of the hh channel.

Observed yields in the boost_1_1J signal region category of the hh channel.

Observed yields in the boost_1_ge2J signal region category of the hh channel.

Observed yields in the boost_1_ge2J signal region category of the hh channel.

Observed yields in the boost_2 signal region category of the hh channel.

Observed yields in the boost_2 signal region category of the hh channel.

Observed yields in the boost_3 signal region category of the hh channel.

Observed yields in the boost_3 signal region category of the hh channel.

Observed yields in the ttH_0 signal region category of the hh channel.

Observed yields in the ttH_0 signal region category of the hh channel.

Observed yields in the ttH_1 signal region category of the hh channel.

Observed yields in the ttH_1 signal region category of the hh channel.

Observed yields in the VH_0 signal region category of the hh channel.

Observed yields in the VH_0 signal region category of the hh channel.

Observed yields in the VH_1 signal region category of the hh channel.

Observed yields in the VH_1 signal region category of the hh channel.

Observed yields in the VBF_0 signal region category of the hh channel.

Observed yields in the VBF_0 signal region category of the hh channel.

Observed yields in the VBF_1 signal region category of the hh channel.

Observed yields in the VBF_1 signal region category of the hh channel.

Observed yields in the boost_0_1J signal region category of the lh channel.

Observed yields in the boost_0_1J signal region category of the lh channel.

Observed yields in the boost_0_ge2J signal region category of the lh channel.

Observed yields in the boost_0_ge2J signal region category of the lh channel.

Observed yields in the boost_1_1J signal region category of the lh channel.

Observed yields in the boost_1_1J signal region category of the lh channel.

Observed yields in the boost_1_ge2J signal region category of the lh channel.

Observed yields in the boost_1_ge2J signal region category of the lh channel.

Observed yields in the boost_2 signal region category of the lh channel.

Observed yields in the boost_2 signal region category of the lh channel.

Observed yields in the boost_3 signal region category of the lh channel.

Observed yields in the boost_3 signal region category of the lh channel.

Observed yields in the VH_0 signal region category of the lh channel.

Observed yields in the VH_0 signal region category of the lh channel.

Observed yields in the VH_1 signal region category of the lh channel.

Observed yields in the VH_1 signal region category of the lh channel.

Observed yields in the VBF_0 signal region category of the lh channel.

Observed yields in the VBF_0 signal region category of the lh channel.

Observed yields in the VBF_1 signal region category of the lh channel.

Observed yields in the VBF_1 signal region category of the lh channel.

Observed yields in the boost_0_1J signal region category of the ll channel.

Observed yields in the boost_0_1J signal region category of the ll channel.

Observed yields in the boost_0_ge2J signal region category of the ll channel.

Observed yields in the boost_0_ge2J signal region category of the ll channel.

Observed yields in the boost_1_1J signal region category of the ll channel.

Observed yields in the boost_1_1J signal region category of the ll channel.

Observed yields in the boost_1_ge2J signal region category of the ll channel.

Observed yields in the boost_1_ge2J signal region category of the ll channel.

Observed yields in the boost_2 signal region category of the ll channel.

Observed yields in the boost_2 signal region category of the ll channel.

Observed yields in the boost_3 signal region category of the ll channel.

Observed yields in the boost_3 signal region category of the ll channel.

Observed yields in the VH_0 signal region category of the ll channel.

Observed yields in the VH_0 signal region category of the ll channel.

Observed yields in the VH_1 signal region category of the ll channel.

Observed yields in the VH_1 signal region category of the ll channel.

Observed yields in the VBF_0 signal region category of the ll channel.

Observed yields in the VBF_0 signal region category of the ll channel.

Observed yields in the VBF_1 signal region category of the ll channel.

Observed yields in the VBF_1 signal region category of the ll channel.

Best-fit values and uncertainties for the pp $\rightarrow H\rightarrow\tau\tau$ cross-section measurement and the measurement in the four dominant production modes. All measurements include the branching ratio of $H\rightarrow\tau\tau$ and are performed with true Higgs boson rapidity $|y_{H}|<2.5$. The SM predictions for each region, computed using the inclusive cross-section calculations and the simulated event samples are also shown. The contributions to the total uncertainty in the measurements from statistical (Stat. unc.) or systematic uncertainties (Syst. unc.) are given separately.

Best-fit values and uncertainties for the pp $\rightarrow H\rightarrow\tau\tau$ cross-section measurement and the measurement in the four dominant production modes. All measurements include the branching ratio of $H\rightarrow\tau\tau$ and are performed with true Higgs boson rapidity $|y_{H}|<2.5$. The SM predictions for each region, computed using the inclusive cross-section calculations and the simulated event samples are also shown. The contributions to the total uncertainty in the measurements from statistical (Stat. unc.) or systematic uncertainties (Syst. unc.) are given separately.

The measured correlations between each parameter of interest in the measurement of the cross-sections per production mode

The measured correlations between each parameter of interest in the measurement of the cross-sections per production mode

Best-fit values and uncertainties for the $H\rightarrow\tau\tau$ cross-sections, in the reduced stage 1.2 STXS scheme. The EW production mode includes vector-boson fusion and qq$\rightarrow$V($\rightarrow$qq)H processes. All measurements include the branching ratio of $H\rightarrow\tau\tau$ and are performed with true Higgs boson rapidity $|y_{H}|<2.5$. The SM predictions for each region, computed using the inclusive cross-section calculations and the simulated event samples are also shown. The contributions to the total uncertainty in the measurements from statistical (Stat. unc.) or systematic uncertainties (Syst. unc.) are given separately. The asterisk symbol (*) indicates that the criteria for m$_{jj}$ only apply to events with at least two reconstructed jets.

Best-fit values and uncertainties for the $H\rightarrow\tau\tau$ cross-sections, in the reduced stage 1.2 STXS scheme. The EW production mode includes vector-boson fusion and qq$\rightarrow$V($\rightarrow$qq)H processes. All measurements include the branching ratio of $H\rightarrow\tau\tau$ and are performed with true Higgs boson rapidity $|y_{H}|<2.5$. The SM predictions for each region, computed using the inclusive cross-section calculations and the simulated event samples are also shown. The contributions to the total uncertainty in the measurements from statistical (Stat. unc.) or systematic uncertainties (Syst. unc.) are given separately. The asterisk symbol (*) indicates that the criteria for m$_{jj}$ only apply to events with at least two reconstructed jets.

The measured correlations between each pair of parameters of interest in the STXS measurement. The asterisk symbol (*) indicates that the criteria for mjj only apply to events with at least two reconstructed jets.

The measured correlations between each pair of parameters of interest in the STXS measurement. The asterisk symbol (*) indicates that the criteria for mjj only apply to events with at least two reconstructed jets.

The BDT distribution of the di-Higgs ggF signal for two different values of $\kappa_{\lambda}$ and the main backgrounds in the low mass region ($m^{*}_{b\bar{b}\gamma\gamma} < 350$ GeV). Distributions are normalized to unit area. The dotted lines denote the category boundaries. Events with a BDT score below 0.881 in the low mass region are discarded.

The BDT distribution (with x-axis zoomed in) of the di-Higgs ggF signal for two different values of $\kappa_{\lambda}$ and the main backgrounds in the low mass region ($m^{*}_{b\bar{b}\gamma\gamma} < 350$ GeV). Distributions are normalized to unit area. The dotted lines denote the category boundaries. Events with a BDT score below 0.881 in the low mass region are discarded. The range of BDT scores is from 0.8 to 1.

The BDT distribution (with x-axis zoomed in) of the di-Higgs ggF signal for two different values of $\kappa_{\lambda}$ and the main backgrounds in the low mass region ($m^{*}_{b\bar{b}\gamma\gamma} < 350$ GeV). Distributions are normalized to unit area. The dotted lines denote the category boundaries. Events with a BDT score below 0.881 in the low mass region are discarded. The range of BDT scores is from 0.8 to 1.

The BDT distribution (with x-axis zoomed in) of the di-Higgs ggF signal for two different values of $\kappa_{\lambda}$ and the main backgrounds in the low mass region ($m^{*}_{b\bar{b}\gamma\gamma} < 350$ GeV). Distributions are normalized to unit area. The dotted lines denote the category boundaries. Events with a BDT score below 0.881 in the low mass region are discarded. The range of BDT scores is from 0.8 to 1.

The BDT distribution (with x-axis zoomed in) of the di-Higgs ggF signal for two different values of $\kappa_{\lambda}$ and the main backgrounds in the low mass region ($m^{*}_{b\bar{b}\gamma\gamma} < 350$ GeV). Distributions are normalized to unit area. The dotted lines denote the category boundaries. Events with a BDT score below 0.881 in the low mass region are discarded. The range of BDT scores is from 0.8 to 1.

The BDT distribution of the di-Higgs ggF signal for two different values of $\kappa_{\lambda}$ and the main backgrounds in the high mass region ($m^{*}_{b\bar{b}\gamma\gamma} > 350$ GeV). Distributions are normalized to unit area. The dotted lines denote the category boundaries. Events with a BDT score below 0.857 in the high mass region are discarded.

The BDT distribution of the di-Higgs ggF signal for two different values of $\kappa_{\lambda}$ and the main backgrounds in the high mass region ($m^{*}_{b\bar{b}\gamma\gamma} > 350$ GeV). Distributions are normalized to unit area. The dotted lines denote the category boundaries. Events with a BDT score below 0.857 in the high mass region are discarded.

The BDT distribution of the di-Higgs ggF signal for two different values of $\kappa_{\lambda}$ and the main backgrounds in the high mass region ($m^{*}_{b\bar{b}\gamma\gamma} > 350$ GeV). Distributions are normalized to unit area. The dotted lines denote the category boundaries. Events with a BDT score below 0.857 in the high mass region are discarded.

The BDT distribution of the di-Higgs ggF signal for two different values of $\kappa_{\lambda}$ and the main backgrounds in the high mass region ($m^{*}_{b\bar{b}\gamma\gamma} > 350$ GeV). Distributions are normalized to unit area. The dotted lines denote the category boundaries. Events with a BDT score below 0.857 in the high mass region are discarded.

The BDT distribution (with x-axis zoomed in) of the di-Higgs ggF signal for two different values of $\kappa_{\lambda}$ and the main backgrounds in the high mass region ($m^{*}_{b\bar{b}\gamma\gamma} > 350$ GeV). Distributions are normalized to unit area. The dotted lines denote the category boundaries. Events with a BDT score below 0.857 in the high mass region are discarded. The range of BDT scores is from 0.8 to 1.

The BDT distribution (with x-axis zoomed in) of the di-Higgs ggF signal for two different values of $\kappa_{\lambda}$ and the main backgrounds in the high mass region ($m^{*}_{b\bar{b}\gamma\gamma} > 350$ GeV). Distributions are normalized to unit area. The dotted lines denote the category boundaries. Events with a BDT score below 0.857 in the high mass region are discarded. The range of BDT scores is from 0.8 to 1.

The BDT distribution (with x-axis zoomed in) of the di-Higgs ggF signal for two different values of $\kappa_{\lambda}$ and the main backgrounds in the high mass region ($m^{*}_{b\bar{b}\gamma\gamma} > 350$ GeV). Distributions are normalized to unit area. The dotted lines denote the category boundaries. Events with a BDT score below 0.857 in the high mass region are discarded. The range of BDT scores is from 0.8 to 1.

The BDT distribution (with x-axis zoomed in) of the di-Higgs ggF signal for two different values of $\kappa_{\lambda}$ and the main backgrounds in the high mass region ($m^{*}_{b\bar{b}\gamma\gamma} > 350$ GeV). Distributions are normalized to unit area. The dotted lines denote the category boundaries. Events with a BDT score below 0.857 in the high mass region are discarded. The range of BDT scores is from 0.8 to 1.

The $BDT_{tot}$ score for the benchmark signal $m_{X}$ = 300 GeV and for the main backgrounds. Distributions are normalized to unit area. The dotted line denotes the event selection threshold. Events with a $BDT_{tot}$ score below 0.85 for $m_{X}$ = 300 GeV are discarded.

The $BDT_{tot}$ score for the benchmark signal $m_{X}$ = 300 GeV and for the main backgrounds. Distributions are normalized to unit area. The dotted line denotes the event selection threshold. Events with a $BDT_{tot}$ score below 0.85 for $m_{X}$ = 300 GeV are discarded.

The $BDT_{tot}$ score for the benchmark signal $m_{X}$ = 300 GeV and for the main backgrounds. Distributions are normalized to unit area. The dotted line denotes the event selection threshold. Events with a $BDT_{tot}$ score below 0.85 for $m_{X}$ = 300 GeV are discarded.

The $BDT_{tot}$ score for the benchmark signal $m_{X}$ = 300 GeV and for the main backgrounds. Distributions are normalized to unit area. The dotted line denotes the event selection threshold. Events with a $BDT_{tot}$ score below 0.85 for $m_{X}$ = 300 GeV are discarded.

The $BDT_{tot}$ score for the benchmark signal $m_{X}$ = 500 GeV and for the main backgrounds. Distributions are normalized to unit area. The dotted line denotes the event selection threshold. Events with a $BDT_{tot}$ score below 0.75 for $m_{X}$ = 500 GeV are discarded.

The $BDT_{tot}$ score for the benchmark signal $m_{X}$ = 500 GeV and for the main backgrounds. Distributions are normalized to unit area. The dotted line denotes the event selection threshold. Events with a $BDT_{tot}$ score below 0.75 for $m_{X}$ = 500 GeV are discarded.

The $BDT_{tot}$ score for the benchmark signal $m_{X}$ = 500 GeV and for the main backgrounds. Distributions are normalized to unit area. The dotted line denotes the event selection threshold. Events with a $BDT_{tot}$ score below 0.75 for $m_{X}$ = 500 GeV are discarded.

The $BDT_{tot}$ score for the benchmark signal $m_{X}$ = 500 GeV and for the main backgrounds. Distributions are normalized to unit area. The dotted line denotes the event selection threshold. Events with a $BDT_{tot}$ score below 0.75 for $m_{X}$ = 500 GeV are discarded.

Distributions of $m_{\gamma\gamma}$ in high mass BDT tight category for the nonresonant $HH$ search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband.

Distributions of $m_{\gamma\gamma}$ in high mass BDT tight category for the nonresonant $HH$ search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband.

Distributions of $m_{\gamma\gamma}$ in high mass BDT tight category for the nonresonant $HH$ search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband.

Distributions of $m_{\gamma\gamma}$ in high mass BDT tight category for the nonresonant $HH$ search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband.

Distributions of $m_{\gamma\gamma}$ in high mass BDT loose category for the nonresonant $HH$ search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband.

Distributions of $m_{\gamma\gamma}$ in high mass BDT loose category for the nonresonant $HH$ search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband.

Distributions of $m_{\gamma\gamma}$ in high mass BDT loose category for the nonresonant $HH$ search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband.

Distributions of $m_{\gamma\gamma}$ in high mass BDT loose category for the nonresonant $HH$ search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband.

Distributions of $m_{\gamma\gamma}$ in low mass BDT tight category for the nonresonant $HH$ search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband.

Distributions of $m_{\gamma\gamma}$ in low mass BDT tight category for the nonresonant $HH$ search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband.

Distributions of $m_{\gamma\gamma}$ in low mass BDT tight category for the nonresonant $HH$ search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband.

Distributions of $m_{\gamma\gamma}$ in low mass BDT tight category for the nonresonant $HH$ search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband.

Distributions of $m_{\gamma\gamma}$ in low mass BDT loose category for the nonresonant $HH$ search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband.

Distributions of $m_{\gamma\gamma}$ in low mass BDT loose category for the nonresonant $HH$ search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband.

Distributions of $m_{\gamma\gamma}$ in low mass BDT loose category for the nonresonant $HH$ search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband.

Distributions of $m_{\gamma\gamma}$ in low mass BDT loose category for the nonresonant $HH$ search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband.

Distributions of $m_{\gamma\gamma}$ for the selections used for the resonance mass point $m_{X}$ = 300 GeV for the resonant search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband. The scalar resonance signal is scaled to a total production cross section $\sigma(pp \rightarrow X \rightarrow HH)$ = 370 fb.

Distributions of $m_{\gamma\gamma}$ for the selections used for the resonance mass point $m_{X}$ = 300 GeV for the resonant search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband. The scalar resonance signal is scaled to a total production cross section $\sigma(pp \rightarrow X \rightarrow HH)$ = 370 fb.

Distributions of $m_{\gamma\gamma}$ for the selections used for the resonance mass point $m_{X}$ = 300 GeV for the resonant search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband. The scalar resonance signal is scaled to a total production cross section $\sigma(pp \rightarrow X \rightarrow HH)$ = 370 fb.

Distributions of $m_{\gamma\gamma}$ for the selections used for the resonance mass point $m_{X}$ = 300 GeV for the resonant search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband. The scalar resonance signal is scaled to a total production cross section $\sigma(pp \rightarrow X \rightarrow HH)$ = 370 fb.

Distributions of $m_{\gamma\gamma}$ for the selections used for the resonance mass point $m_{X}$ = 500 GeV for the resonant search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband. The scalar resonance signal is scaled to a total production cross section $\sigma(pp \rightarrow X \rightarrow HH)$ = 67 fb.

Distributions of $m_{\gamma\gamma}$ for the selections used for the resonance mass point $m_{X}$ = 500 GeV for the resonant search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband. The scalar resonance signal is scaled to a total production cross section $\sigma(pp \rightarrow X \rightarrow HH)$ = 67 fb.

Distributions of $m_{\gamma\gamma}$ for the selections used for the resonance mass point $m_{X}$ = 500 GeV for the resonant search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband. The scalar resonance signal is scaled to a total production cross section $\sigma(pp \rightarrow X \rightarrow HH)$ = 67 fb.

Distributions of $m_{\gamma\gamma}$ for the selections used for the resonance mass point $m_{X}$ = 500 GeV for the resonant search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband. The scalar resonance signal is scaled to a total production cross section $\sigma(pp \rightarrow X \rightarrow HH)$ = 67 fb.

The number of data events observed in the 120 GeV < $m_{\gamma\gamma}$ < 130 GeV window, the number of $HH$ signal events expected for $\kappa_{\lambda}$ = 1 and for $\kappa_{\lambda}$ = 10, and events expected for single Higgs boson production (estimated using MC simulation), as well as for continuum background. For the single Higgs boson, Rest includes VBF, $WH$, $tHqb$, and $tHW$. The values are obtained from a fit of the Asimov data set generated under the SM signal-plus-background hypothesis, $\kappa_{\lambda}$ = 1. The continuum background component of the Asimov data set is obtained from the fit of the data sideband. The uncertainties in $HH$ signals and single Higgs boson background include the systematic uncertainties discussed in Section 6. The uncertainty in the continuum background is given by the sum in quadrature of the statistical uncertainty from the fit to the data and the spurious-signal uncertainty.

The number of data events observed in the 120 GeV < $m_{\gamma\gamma}$ < 130 GeV window, the number of $HH$ signal events expected for $\kappa_{\lambda}$ = 1 and for $\kappa_{\lambda}$ = 10, and events expected for single Higgs boson production (estimated using MC simulation), as well as for continuum background. For the single Higgs boson, Rest includes VBF, $WH$, $tHqb$, and $tHW$. The values are obtained from a fit of the Asimov data set generated under the SM signal-plus-background hypothesis, $\kappa_{\lambda}$ = 1. The continuum background component of the Asimov data set is obtained from the fit of the data sideband. The uncertainties in $HH$ signals and single Higgs boson background include the systematic uncertainties discussed in Section 6. The uncertainty in the continuum background is given by the sum in quadrature of the statistical uncertainty from the fit to the data and the spurious-signal uncertainty.

The number of data events observed in the 120 GeV < $m_{\gamma\gamma}$ < 130 GeV window, the number of $HH$ signal events expected for $\kappa_{\lambda}$ = 1 and for $\kappa_{\lambda}$ = 10, and events expected for single Higgs boson production (estimated using MC simulation), as well as for continuum background. For the single Higgs boson, Rest includes VBF, $WH$, $tHqb$, and $tHW$. The values are obtained from a fit of the Asimov data set generated under the SM signal-plus-background hypothesis, $\kappa_{\lambda}$ = 1. The continuum background component of the Asimov data set is obtained from the fit of the data sideband. The uncertainties in $HH$ signals and single Higgs boson background include the systematic uncertainties discussed in Section 6. The uncertainty in the continuum background is given by the sum in quadrature of the statistical uncertainty from the fit to the data and the spurious-signal uncertainty.

The number of data events observed in the 120 GeV < $m_{\gamma\gamma}$ < 130 GeV window, the number of $HH$ signal events expected for $\kappa_{\lambda}$ = 1 and for $\kappa_{\lambda}$ = 10, and events expected for single Higgs boson production (estimated using MC simulation), as well as for continuum background. For the single Higgs boson, Rest includes VBF, $WH$, $tHqb$, and $tHW$. The values are obtained from a fit of the Asimov data set generated under the SM signal-plus-background hypothesis, $\kappa_{\lambda}$ = 1. The continuum background component of the Asimov data set is obtained from the fit of the data sideband. The uncertainties in $HH$ signals and single Higgs boson background include the systematic uncertainties discussed in Section 6. The uncertainty in the continuum background is given by the sum in quadrature of the statistical uncertainty from the fit to the data and the spurious-signal uncertainty.

Observed and expected limits at 95% CL on the cross section of nonresonant Higgs boson pair production as a function of the Higgs boson self-coupling modifier $\kappa_{\lambda}= \lambda_{HHH}/\lambda^{\textrm{SM}}_{HHH}$. The expected constraints on $\kappa_{\lambda}$ are obtained with a background hypothesis excluding $pp \rightarrow HH$ production. The $\pm 1\sigma$ and $\pm 2\sigma$ variations about the expected limit due to statistical and systematic uncertainties are also shown. The theory prediction curve represents the scenario where all parameters and couplings are set to their SM values except for $\kappa_{\lambda}$. The uncertainty band of the theory prediction curve shows the cross-section uncertainty.

Observed and expected limits at 95% CL on the cross section of nonresonant Higgs boson pair production as a function of the Higgs boson self-coupling modifier $\kappa_{\lambda}= \lambda_{HHH}/\lambda^{\textrm{SM}}_{HHH}$. The expected constraints on $\kappa_{\lambda}$ are obtained with a background hypothesis excluding $pp \rightarrow HH$ production. The $\pm 1\sigma$ and $\pm 2\sigma$ variations about the expected limit due to statistical and systematic uncertainties are also shown. The theory prediction curve represents the scenario where all parameters and couplings are set to their SM values except for $\kappa_{\lambda}$. The uncertainty band of the theory prediction curve shows the cross-section uncertainty.

Observed and expected limits at 95% CL on the cross section of nonresonant Higgs boson pair production as a function of the Higgs boson self-coupling modifier $\kappa_{\lambda}= \lambda_{HHH}/\lambda^{\textrm{SM}}_{HHH}$. The expected constraints on $\kappa_{\lambda}$ are obtained with a background hypothesis excluding $pp \rightarrow HH$ production. The $\pm 1\sigma$ and $\pm 2\sigma$ variations about the expected limit due to statistical and systematic uncertainties are also shown. The theory prediction curve represents the scenario where all parameters and couplings are set to their SM values except for $\kappa_{\lambda}$. The uncertainty band of the theory prediction curve shows the cross-section uncertainty.

Observed and expected limits at 95% CL on the cross section of nonresonant Higgs boson pair production as a function of the Higgs boson self-coupling modifier $\kappa_{\lambda}= \lambda_{HHH}/\lambda^{\textrm{SM}}_{HHH}$. The expected constraints on $\kappa_{\lambda}$ are obtained with a background hypothesis excluding $pp \rightarrow HH$ production. The $\pm 1\sigma$ and $\pm 2\sigma$ variations about the expected limit due to statistical and systematic uncertainties are also shown. The theory prediction curve represents the scenario where all parameters and couplings are set to their SM values except for $\kappa_{\lambda}$. The uncertainty band of the theory prediction curve shows the cross-section uncertainty.

Values of the negative log-profile-likelihood ratio ($-2ln\Lambda$) as a function of $\kappa_{\lambda}$ evaluated for the combination of all the categories of the nonresonant search. The coupling of the Higgs boson to fermions and gauge bosons is set to SM values in the profile likelihood calculation. The Asimov data set is generated under the SM signal-plus-background hypothesis, $\kappa_{\lambda}$= 1. All systematic uncertainties, including the theoretical uncertainties in the di-Higgs boson production cross section, are included. The intersections of the solid curves and the horizontal dashed lines indicate the 1$\sigma$ and 2$\sigma$ confidence-level intervals.

Values of the negative log-profile-likelihood ratio ($-2ln\Lambda$) as a function of $\kappa_{\lambda}$ evaluated for the combination of all the categories of the nonresonant search. The coupling of the Higgs boson to fermions and gauge bosons is set to SM values in the profile likelihood calculation. The Asimov data set is generated under the SM signal-plus-background hypothesis, $\kappa_{\lambda}$= 1. All systematic uncertainties, including the theoretical uncertainties in the di-Higgs boson production cross section, are included. The intersections of the solid curves and the horizontal dashed lines indicate the 1$\sigma$ and 2$\sigma$ confidence-level intervals.

Values of the negative log-profile-likelihood ratio ($-2ln\Lambda$) as a function of $\kappa_{\lambda}$ evaluated for the combination of all the categories of the nonresonant search. The coupling of the Higgs boson to fermions and gauge bosons is set to SM values in the profile likelihood calculation. The Asimov data set is generated under the SM signal-plus-background hypothesis, $\kappa_{\lambda}$= 1. All systematic uncertainties, including the theoretical uncertainties in the di-Higgs boson production cross section, are included. The intersections of the solid curves and the horizontal dashed lines indicate the 1$\sigma$ and 2$\sigma$ confidence-level intervals.

Values of the negative log-profile-likelihood ratio ($-2ln\Lambda$) as a function of $\kappa_{\lambda}$ evaluated for the combination of all the categories of the nonresonant search. The coupling of the Higgs boson to fermions and gauge bosons is set to SM values in the profile likelihood calculation. The Asimov data set is generated under the SM signal-plus-background hypothesis, $\kappa_{\lambda}$= 1. All systematic uncertainties, including the theoretical uncertainties in the di-Higgs boson production cross section, are included. The intersections of the solid curves and the horizontal dashed lines indicate the 1$\sigma$ and 2$\sigma$ confidence-level intervals.

The number of events observed in the 120 < $m_{\gamma\gamma}$ < 130 GeV window in data, the number of events expected for scalar resonance signals of masses $m_{X}$ = 300 GeV and $m_{X}$ = 500 GeV assuming a total production cross section $\sigma(pp \rightarrow X \rightarrow HH)$ equal to the observed exclusion limits of Figure 15, and events expected for SM $HH$ and single Higgs boson production (estimated using MC simulation), as well as for continuum background. The values are obtained from a fit of the Asimov data set generated under the signal-plus-background hypothesis. The continuum background component of the Asimov data set is obtained from the fit of the data sideband. The uncertainties in the resonant signals and the SM $HH$ and single-Higgs-boson backgrounds include the systematic uncertainties discussed in Section 6. The uncertainty in the continuum background is given by the sum in quadrature of the statistical uncertainty from the fit to the data and the spurious-signal uncertainty.

The number of events observed in the 120 < $m_{\gamma\gamma}$ < 130 GeV window in data, the number of events expected for scalar resonance signals of masses $m_{X}$ = 300 GeV and $m_{X}$ = 500 GeV assuming a total production cross section $\sigma(pp \rightarrow X \rightarrow HH)$ equal to the observed exclusion limits of Figure 15, and events expected for SM $HH$ and single Higgs boson production (estimated using MC simulation), as well as for continuum background. The values are obtained from a fit of the Asimov data set generated under the signal-plus-background hypothesis. The continuum background component of the Asimov data set is obtained from the fit of the data sideband. The uncertainties in the resonant signals and the SM $HH$ and single-Higgs-boson backgrounds include the systematic uncertainties discussed in Section 6. The uncertainty in the continuum background is given by the sum in quadrature of the statistical uncertainty from the fit to the data and the spurious-signal uncertainty.

The number of events observed in the 120 < $m_{\gamma\gamma}$ < 130 GeV window in data, the number of events expected for scalar resonance signals of masses $m_{X}$ = 300 GeV and $m_{X}$ = 500 GeV assuming a total production cross section $\sigma(pp \rightarrow X \rightarrow HH)$ equal to the observed exclusion limits of Figure 15, and events expected for SM $HH$ and single Higgs boson production (estimated using MC simulation), as well as for continuum background. The values are obtained from a fit of the Asimov data set generated under the signal-plus-background hypothesis. The continuum background component of the Asimov data set is obtained from the fit of the data sideband. The uncertainties in the resonant signals and the SM $HH$ and single-Higgs-boson backgrounds include the systematic uncertainties discussed in Section 6. The uncertainty in the continuum background is given by the sum in quadrature of the statistical uncertainty from the fit to the data and the spurious-signal uncertainty.

The number of events observed in the 120 < $m_{\gamma\gamma}$ < 130 GeV window in data, the number of events expected for scalar resonance signals of masses $m_{X}$ = 300 GeV and $m_{X}$ = 500 GeV assuming a total production cross section $\sigma(pp \rightarrow X \rightarrow HH)$ equal to the observed exclusion limits of Figure 15, and events expected for SM $HH$ and single Higgs boson production (estimated using MC simulation), as well as for continuum background. The values are obtained from a fit of the Asimov data set generated under the signal-plus-background hypothesis. The continuum background component of the Asimov data set is obtained from the fit of the data sideband. The uncertainties in the resonant signals and the SM $HH$ and single-Higgs-boson backgrounds include the systematic uncertainties discussed in Section 6. The uncertainty in the continuum background is given by the sum in quadrature of the statistical uncertainty from the fit to the data and the spurious-signal uncertainty.

Observed and expected limits at 95% CL on the production cross section of a narrow-width scalar resonance $X$ as a function of the mass $m_{X}$ of the hypothetical scalar particle. The black solid line represents the observed upper limits. The dashed line represents the expected upper limits. The $\pm 1\sigma$ and $\pm 2\sigma$ variations about the expected limit due to statistical and systematic uncertainties are also shown.

Observed and expected limits at 95% CL on the production cross section of a narrow-width scalar resonance $X$ as a function of the mass $m_{X}$ of the hypothetical scalar particle. The black solid line represents the observed upper limits. The dashed line represents the expected upper limits. The $\pm 1\sigma$ and $\pm 2\sigma$ variations about the expected limit due to statistical and systematic uncertainties are also shown.

Observed and expected limits at 95% CL on the production cross section of a narrow-width scalar resonance $X$ as a function of the mass $m_{X}$ of the hypothetical scalar particle. The black solid line represents the observed upper limits. The dashed line represents the expected upper limits. The $\pm 1\sigma$ and $\pm 2\sigma$ variations about the expected limit due to statistical and systematic uncertainties are also shown.

Observed and expected limits at 95% CL on the production cross section of a narrow-width scalar resonance $X$ as a function of the mass $m_{X}$ of the hypothetical scalar particle. The black solid line represents the observed upper limits. The dashed line represents the expected upper limits. The $\pm 1\sigma$ and $\pm 2\sigma$ variations about the expected limit due to statistical and systematic uncertainties are also shown.

Breakdown of the dominant systematic uncertainties. The impact of the uncertainties is defined according to the statistical analysis described in Section 7. It corresponds to the relative variation of the expected upper limit on the cross section when re-evaluating the profile likelihood ratio after fixing the nuisance parameter in question to its best-fit value, while all remaining nuisance parameters remain free to float. The impact is shown in %. Only systematic uncertainties with an impact of at least 0.2% are shown. Uncertainties of the "Norm. + Shape" type affect both the normalization and the parameters of the functional form. The rest of the uncertainties affect only the yields.

Breakdown of the dominant systematic uncertainties. The impact of the uncertainties is defined according to the statistical analysis described in Section 7. It corresponds to the relative variation of the expected upper limit on the cross section when re-evaluating the profile likelihood ratio after fixing the nuisance parameter in question to its best-fit value, while all remaining nuisance parameters remain free to float. The impact is shown in %. Only systematic uncertainties with an impact of at least 0.2% are shown. Uncertainties of the "Norm. + Shape" type affect both the normalization and the parameters of the functional form. The rest of the uncertainties affect only the yields.

Breakdown of the dominant systematic uncertainties. The impact of the uncertainties is defined according to the statistical analysis described in Section 7. It corresponds to the relative variation of the expected upper limit on the cross section when re-evaluating the profile likelihood ratio after fixing the nuisance parameter in question to its best-fit value, while all remaining nuisance parameters remain free to float. The impact is shown in %. Only systematic uncertainties with an impact of at least 0.2% are shown. Uncertainties of the "Norm. + Shape" type affect both the normalization and the parameters of the functional form. The rest of the uncertainties affect only the yields.

Breakdown of the dominant systematic uncertainties. The impact of the uncertainties is defined according to the statistical analysis described in Section 7. It corresponds to the relative variation of the expected upper limit on the cross section when re-evaluating the profile likelihood ratio after fixing the nuisance parameter in question to its best-fit value, while all remaining nuisance parameters remain free to float. The impact is shown in %. Only systematic uncertainties with an impact of at least 0.2% are shown. Uncertainties of the "Norm. + Shape" type affect both the normalization and the parameters of the functional form. The rest of the uncertainties affect only the yields.

Cutflow for nonresonant di-Higgs ggF signal sample, yields are normalized to 139 $fb^{-1}$.

Cutflow for nonresonant di-Higgs ggF signal sample, yields are normalized to 139 $fb^{-1}$.

Cutflow for nonresonant di-Higgs ggF signal sample, yields are normalized to 139 $fb^{-1}$.

Cutflow for nonresonant di-Higgs ggF signal sample, yields are normalized to 139 $fb^{-1}$.

Cutflow for resonant signal sample, with $m_{X}$ = 300 GeV, yields are normalized to 139 $fb^{-1}$.

Cutflow for resonant signal sample, with $m_{X}$ = 300 GeV, yields are normalized to 139 $fb^{-1}$.

Cutflow for resonant signal sample, with $m_{X}$ = 300 GeV, yields are normalized to 139 $fb^{-1}$.

Cutflow for resonant signal sample, with $m_{X}$ = 300 GeV, yields are normalized to 139 $fb^{-1}$.

Cutflow for resonant signal sample, with $m_{X}$ = 500 GeV, yields are normalized to 139 $fb^{-1}$.

Cutflow for resonant signal sample, with $m_{X}$ = 500 GeV, yields are normalized to 139 $fb^{-1}$.

Cutflow for resonant signal sample, with $m_{X}$ = 500 GeV, yields are normalized to 139 $fb^{-1}$.

Cutflow for resonant signal sample, with $m_{X}$ = 500 GeV, yields are normalized to 139 $fb^{-1}$.

Comparison of $m_{b\bar{b}}$ distributions when applying the specific b-jet energy calibration and the nominal jet energy calibration. The distributions are fitted using a Bukin function, and the values of the peak position, resolution and the relative improvement are reported in the legend.

Comparison of $m_{b\bar{b}}$ distributions when applying the specific b-jet energy calibration and the nominal jet energy calibration. The distributions are fitted using a Bukin function, and the values of the peak position, resolution and the relative improvement are reported in the legend.

Comparison of $m_{b\bar{b}}$ distributions when applying the specific b-jet energy calibration and the nominal jet energy calibration. The distributions are fitted using a Bukin function, and the values of the peak position, resolution and the relative improvement are reported in the legend.

Comparison of $m_{b\bar{b}}$ distributions when applying the specific b-jet energy calibration and the nominal jet energy calibration. The distributions are fitted using a Bukin function, and the values of the peak position, resolution and the relative improvement are reported in the legend.

Fit results of $m_{b\bar{b}}$ distributions when applying the specific b-jet energy calibration and the nominal jet energy calibration. The distributions are fitted using a Bukin function, and the values of the peak position, resolution and the relative improvement are reported in the legend.

Fit results of $m_{b\bar{b}}$ distributions when applying the specific b-jet energy calibration and the nominal jet energy calibration. The distributions are fitted using a Bukin function, and the values of the peak position, resolution and the relative improvement are reported in the legend.

Fit results of $m_{b\bar{b}}$ distributions when applying the specific b-jet energy calibration and the nominal jet energy calibration. The distributions are fitted using a Bukin function, and the values of the peak position, resolution and the relative improvement are reported in the legend.

Fit results of $m_{b\bar{b}}$ distributions when applying the specific b-jet energy calibration and the nominal jet energy calibration. The distributions are fitted using a Bukin function, and the values of the peak position, resolution and the relative improvement are reported in the legend.

The relative amount (purity) of expected events from SM $HH$ and single Higgs boson production processes for each of the four categories of the nonresonant search. The Higgs boson pair production with $k_{\lambda} = 1$ is considered as signal in (a), while the case with $k_{\lambda} = 10$ is considered as signal in (b).

The relative amount (purity) of expected events from SM $HH$ and single Higgs boson production processes for each of the four categories of the nonresonant search. The Higgs boson pair production with $k_{\lambda} = 1$ is considered as signal in (a), while the case with $k_{\lambda} = 10$ is considered as signal in (b).

The relative amount (purity) of expected events from SM $HH$ and single Higgs boson production processes for each of the four categories of the nonresonant search. The Higgs boson pair production with $k_{\lambda} = 1$ is considered as signal in (a), while the case with $k_{\lambda} = 10$ is considered as signal in (b).

The relative amount (purity) of expected events from SM $HH$ and single Higgs boson production processes for each of the four categories of the nonresonant search. The Higgs boson pair production with $k_{\lambda} = 1$ is considered as signal in (a), while the case with $k_{\lambda} = 10$ is considered as signal in (b).

The expected significance in each of the four categories of the nonresonant search. The Higgs boson pair production with $k_{\lambda} = 1$ is considered as signal in (a), while the case with $k_{\lambda} = 10$ is considered as signal in (b). The single Higgs boson processes and the di-photon continuum spectrum are considered as background.

The expected significance in each of the four categories of the nonresonant search. The Higgs boson pair production with $k_{\lambda} = 1$ is considered as signal in (a), while the case with $k_{\lambda} = 10$ is considered as signal in (b). The single Higgs boson processes and the di-photon continuum spectrum are considered as background.

The expected significance in each of the four categories of the nonresonant search. The Higgs boson pair production with $k_{\lambda} = 1$ is considered as signal in (a), while the case with $k_{\lambda} = 10$ is considered as signal in (b). The single Higgs boson processes and the di-photon continuum spectrum are considered as background.

The expected significance in each of the four categories of the nonresonant search. The Higgs boson pair production with $k_{\lambda} = 1$ is considered as signal in (a), while the case with $k_{\lambda} = 10$ is considered as signal in (b). The single Higgs boson processes and the di-photon continuum spectrum are considered as background.

Spurious signal result for the exponential pdf for the various ggF nonresonant di-Higgs categories. In each category, the spurious signal value ($n_{sp}$) and its ratio to the expected statistical error ($Z_{spur}$) from data are shown.

Spurious signal result for the exponential pdf for the various ggF nonresonant di-Higgs categories. In each category, the spurious signal value ($n_{sp}$) and its ratio to the expected statistical error ($Z_{spur}$) from data are shown.

Spurious signal result for the exponential pdf for the various ggF nonresonant di-Higgs categories. In each category, the spurious signal value ($n_{sp}$) and its ratio to the expected statistical error ($Z_{spur}$) from data are shown.

Spurious signal result for the exponential pdf for the various ggF nonresonant di-Higgs categories. In each category, the spurious signal value ($n_{sp}$) and its ratio to the expected statistical error ($Z_{spur}$) from data are shown.

Spurious signal result for the exponential pdf as function of the resonant di-Higgs signal mass. The spurious signal value and its ratio to the expected statistical error from data are shown.

Spurious signal result for the exponential pdf as function of the resonant di-Higgs signal mass. The spurious signal value and its ratio to the expected statistical error from data are shown.

Spurious signal result for the exponential pdf as function of the resonant di-Higgs signal mass. The spurious signal value and its ratio to the expected statistical error from data are shown.

Spurious signal result for the exponential pdf as function of the resonant di-Higgs signal mass. The spurious signal value and its ratio to the expected statistical error from data are shown.

Distributions of the signal efficiency as a function of $\kappa_{\lambda}$, for the di-Higgs boson ggF nonresonant production mode. The range of $\kappa_{\lambda}$ in the table is from -10 to 10.

Distributions of the signal efficiency as a function of $\kappa_{\lambda}$, for the di-Higgs boson ggF nonresonant production mode. The range of $\kappa_{\lambda}$ in the table is from -10 to 10.

Distributions of the signal efficiency as a function of $\kappa_{\lambda}$, for the di-Higgs boson ggF nonresonant production mode. The range of $\kappa_{\lambda}$ in the table is from -10 to 10.

Distributions of the signal efficiency as a function of $\kappa_{\lambda}$, for the di-Higgs boson ggF nonresonant production mode. The range of $\kappa_{\lambda}$ in the table is from -10 to 10.

Distributions of the signal efficiency as a function of $\kappa_{\lambda}$, for the di-Higgs boson VBF nonresonant production mode. The range of $\kappa_{\lambda}$ in the table is from -10 to 10.

Distributions of the signal efficiency as a function of $\kappa_{\lambda}$, for the di-Higgs boson VBF nonresonant production mode. The range of $\kappa_{\lambda}$ in the table is from -10 to 10.

Distributions of the signal efficiency as a function of $\kappa_{\lambda}$, for the di-Higgs boson VBF nonresonant production mode. The range of $\kappa_{\lambda}$ in the table is from -10 to 10.

Distributions of the signal efficiency as a function of $\kappa_{\lambda}$, for the di-Higgs boson VBF nonresonant production mode. The range of $\kappa_{\lambda}$ in the table is from -10 to 10.

Values of the negative log-profile-likelihood ($-2ln\Lambda$) as a function of $\kappa_{\lambda}$ evaluated for the combination of all the categories of the nonresonant search. The coupling of the Higgs boson to fermions and gauge bosons is set to SM values in the profile likelihood calculation. The Asimov data set is generated under the SM signal-plus-background hypothesis, $\kappa_{\lambda}$= 1. All systematic uncertainties, including the theoretical uncertainties on the di-Higgs boson production cross section, are included. The intersections of the solid curves and the horizontal dashed lines indicate the 1$\sigma$ and 2$\sigma$ confidence level intervals. The best fit value corresponds to $\kappa_{\lambda}$ = $2.8^{+2.0}_{-2.2}(^{+3.8}_{-4.3})$ for the 1$\sigma$(2$\sigma$) confidence interval. The expected value corresponds to $\kappa_{\lambda}$ = $1.0^{+5.5}_{-2.4}(^{+7.3}_{-4.2})$ for the 1$\sigma$(2$\sigma$) confidence interval. The dashed curves represent values of the negative log-profile-likelihood where the Higgs boson branching fractions and the cross section of the production modes are varied as a function of $\kappa_{\lambda}$. In this case,the best fit value corresponds to $\kappa_{\lambda}$ = $2.7^{+2.0}_{-2.2}(^{+3.8}_{-4.3})$ and the expected value corresponds to $\kappa_{\lambda}$ = $1.0^{+5.4}_{-2.5}(^{+7.3}_{-4.3})$ for the 1$\sigma$(2$\sigma$) confidence interval.

Values of the negative log-profile-likelihood ($-2ln\Lambda$) as a function of $\kappa_{\lambda}$ evaluated for the combination of all the categories of the nonresonant search. The coupling of the Higgs boson to fermions and gauge bosons is set to SM values in the profile likelihood calculation. The Asimov data set is generated under the SM signal-plus-background hypothesis, $\kappa_{\lambda}$= 1. All systematic uncertainties, including the theoretical uncertainties on the di-Higgs boson production cross section, are included. The intersections of the solid curves and the horizontal dashed lines indicate the 1$\sigma$ and 2$\sigma$ confidence level intervals. The best fit value corresponds to $\kappa_{\lambda}$ = $2.8^{+2.0}_{-2.2}(^{+3.8}_{-4.3})$ for the 1$\sigma$(2$\sigma$) confidence interval. The expected value corresponds to $\kappa_{\lambda}$ = $1.0^{+5.5}_{-2.4}(^{+7.3}_{-4.2})$ for the 1$\sigma$(2$\sigma$) confidence interval. The dashed curves represent values of the negative log-profile-likelihood where the Higgs boson branching fractions and the cross section of the production modes are varied as a function of $\kappa_{\lambda}$. In this case,the best fit value corresponds to $\kappa_{\lambda}$ = $2.7^{+2.0}_{-2.2}(^{+3.8}_{-4.3})$ and the expected value corresponds to $\kappa_{\lambda}$ = $1.0^{+5.4}_{-2.5}(^{+7.3}_{-4.3})$ for the 1$\sigma$(2$\sigma$) confidence interval.

Values of the negative log-profile-likelihood ($-2ln\Lambda$) as a function of $\kappa_{\lambda}$ evaluated for the combination of all the categories of the nonresonant search. The coupling of the Higgs boson to fermions and gauge bosons is set to SM values in the profile likelihood calculation. The Asimov data set is generated under the SM signal-plus-background hypothesis, $\kappa_{\lambda}$= 1. All systematic uncertainties, including the theoretical uncertainties on the di-Higgs boson production cross section, are included. The intersections of the solid curves and the horizontal dashed lines indicate the 1$\sigma$ and 2$\sigma$ confidence level intervals. The best fit value corresponds to $\kappa_{\lambda}$ = $2.8^{+2.0}_{-2.2}(^{+3.8}_{-4.3})$ for the 1$\sigma$(2$\sigma$) confidence interval. The expected value corresponds to $\kappa_{\lambda}$ = $1.0^{+5.5}_{-2.4}(^{+7.3}_{-4.2})$ for the 1$\sigma$(2$\sigma$) confidence interval. The dashed curves represent values of the negative log-profile-likelihood where the Higgs boson branching fractions and the cross section of the production modes are varied as a function of $\kappa_{\lambda}$. In this case,the best fit value corresponds to $\kappa_{\lambda}$ = $2.7^{+2.0}_{-2.2}(^{+3.8}_{-4.3})$ and the expected value corresponds to $\kappa_{\lambda}$ = $1.0^{+5.4}_{-2.5}(^{+7.3}_{-4.3})$ for the 1$\sigma$(2$\sigma$) confidence interval.

Values of the negative log-profile-likelihood ($-2ln\Lambda$) as a function of $\kappa_{\lambda}$ evaluated for the combination of all the categories of the nonresonant search. The coupling of the Higgs boson to fermions and gauge bosons is set to SM values in the profile likelihood calculation. The Asimov data set is generated under the SM signal-plus-background hypothesis, $\kappa_{\lambda}$= 1. All systematic uncertainties, including the theoretical uncertainties on the di-Higgs boson production cross section, are included. The intersections of the solid curves and the horizontal dashed lines indicate the 1$\sigma$ and 2$\sigma$ confidence level intervals. The best fit value corresponds to $\kappa_{\lambda}$ = $2.8^{+2.0}_{-2.2}(^{+3.8}_{-4.3})$ for the 1$\sigma$(2$\sigma$) confidence interval. The expected value corresponds to $\kappa_{\lambda}$ = $1.0^{+5.5}_{-2.4}(^{+7.3}_{-4.2})$ for the 1$\sigma$(2$\sigma$) confidence interval. The dashed curves represent values of the negative log-profile-likelihood where the Higgs boson branching fractions and the cross section of the production modes are varied as a function of $\kappa_{\lambda}$. In this case,the best fit value corresponds to $\kappa_{\lambda}$ = $2.7^{+2.0}_{-2.2}(^{+3.8}_{-4.3})$ and the expected value corresponds to $\kappa_{\lambda}$ = $1.0^{+5.4}_{-2.5}(^{+7.3}_{-4.3})$ for the 1$\sigma$(2$\sigma$) confidence interval.

Minimum BDT value of the events passing the selection criteria of the resonant search. The combined BDT score is formed using as coefficients $C_{1}$ = 0.65 and $C_{2}$ = 1 − $C_{1}$. The selection efficiency for the resonant $X \rightarrow HH$ signal is also shown.

Minimum BDT value of the events passing the selection criteria of the resonant search. The combined BDT score is formed using as coefficients $C_{1}$ = 0.65 and $C_{2}$ = 1 − $C_{1}$. The selection efficiency for the resonant $X \rightarrow HH$ signal is also shown.

Minimum BDT value of the events passing the selection criteria of the resonant search. The combined BDT score is formed using as coefficients $C_{1}$ = 0.65 and $C_{2}$ = 1 − $C_{1}$. The selection efficiency for the resonant $X \rightarrow HH$ signal is also shown.

Minimum BDT value of the events passing the selection criteria of the resonant search. The combined BDT score is formed using as coefficients $C_{1}$ = 0.65 and $C_{2}$ = 1 − $C_{1}$. The selection efficiency for the resonant $X \rightarrow HH$ signal is also shown.

The $1\sigma_{\text{exp}}$ variation of the expected exclusion contour at 95% CL as a function of the smuon and neutralino masses, for $\lambda_{231}^{'}=1.0$.

The observed exclusion contour at 95% CL as a function of the smuon and neutralino masses, for $\lambda_{231}^{'}=0.1$.

The expected exclusion contour at 95% CL as a function of the smuon and neutralino masses, for $\lambda_{231}^{'}=0.1$.

The observed exclusion contour at 95% CL as a function of the smuon and neutralino masses, for $\lambda_{231}^{'}=0.15$.

The expected exclusion contour at 95% CL as a function of the smuon and neutralino masses, for $\lambda_{231}^{'}=0.15$.

The observed exclusion contour at 95% CL as a function of the smuon and neutralino masses, for $\lambda_{231}^{'}=0.2$.

The expected exclusion contour at 95% CL as a function of the smuon and neutralino masses, for $\lambda_{231}^{'}=0.2$.

The observed exclusion contour at 95% CL as a function of the smuon and neutralino masses, for $\lambda_{231}^{'}=0.4$.

The expected exclusion contour at 95% CL as a function of the smuon and neutralino masses, for $\lambda_{231}^{'}=0.4$.

The observed exclusion contour at 95% CL as a function of the smuon and neutralino masses, for $\lambda_{231}^{'}=0.6$.

The expected exclusion contour at 95% CL as a function of the smuon and neutralino masses, for $\lambda_{231}^{'}=0p6$.

The observed exclusion contour at 95% CL as a function of the smuon and neutralino masses, for $\lambda_{231}^{'}=1.5$.

The expected exclusion contour at 95% CL as a function of the smuon and neutralino masses, for $\lambda_{231}^{'}=1.5$.

The observed exclusion contour at 95% CL as a function of the leptoquark mass and coupling strength.

The expected exclusion contour at 95% CL as a function of the leptoquark mass and coupling strength.

The minus $1\sigma_{\text{theory}}$ variation of the observed exclusion contour at 95% CL as a function of the leptoquark mass and coupling strength.

The plus $1\sigma_{\text{theory}}$ variation of the observed exclusion contour at 95% CL as a function of the leptoquark mass and coupling strength.

The $1\sigma_{\text{exp}}$ variation of the expected exclusion contour at 95% CL as a function of the leptoquark mass and coupling strength.

Observed yields, and fake lepton background yields in the $e^{+}\mu^{-}$ and $e^{-}\mu^{+}$ channels of SR-MET, along with the results of the $e^{+}\mu^{-}/e^{-}\mu^{+}$ ratio measurement and 1-sided p-value in SR-MET, binned in $M_{T2}$.

Observed yields, and fake lepton background yields in the $e^{+}\mu^{-}$ and $e^{-}\mu^{+}$ channels of SR-JET, along with the results of the $e^{+}\mu^{-}/e^{-}\mu^{+}$ ratio measurement and 1-sided p-value in SR-JET, binned in $H_{\text{P}}$.

Observed and expected 95% CL upper limits on the total number of signal events entering the $e^{+}\mu^{-}$ and $e^{-}\mu^{+}$ channels of each bin of SR-MET. The regions are binned in the same way as the ratio $\rho$ measurement. The limits are shown for a selection of 'z' values, where 'z' is the fraction of the total signal events entering the $e^{+}\mu^{-}$ channel.

Observed and expected 95% CL upper limits on the total number of signal events entering the $e^{+}\mu^{-}$ and $e^{-}\mu^{+}$ channels of each bin of SR-JET. The regions are binned in the same way as the ratio $\rho$ measurement. The limits are shown for a selection of 'z' values, where 'z' is the fraction of the total signal events entering the $e^{+}\mu^{-}$ channel.

Signal yields following each cut in the analysis, for representative $R$-parity-violating supersymmetry and leptoquark signals. All yields are MC generator-weighted and normalised to $139~\text{fb}^{-1}$. The cut labelled `Preselection' includes trigger requirements, and requires exactly one Baseline electron and one Baseline muon. At this point, the muon charge-bias correction weights are also applied. The $R$-parity-violating supersymmetry models were generated by specifying a top-quark in the final state and applying a two-lepton filter, hence the first row also includes events where the top quark decays to an electron.

The observed exclusion contours as a function of (m(med), m($\chi$)), with Vector mediator)

The expected exclusion contours as a function of (m(a), tan($\beta$)), with sin($\theta$) = 0.35)

The observed exclusion contours as a function of (m(a), tan($\beta$)), with sin($\theta$) = 0.35)

The expected exclusion contours as a function of (m(a), tan($\beta$)), with sin($\theta$) = 0.7)

The observed exclusion contours as a function of (m(a), tan($\beta$)), with sin($\theta$) = 0.7)

The expected exclusion contours as a function of (m(H), tan($\beta$)), with sin($\theta$) = 0.35)

The observed exclusion contours as a function of (m(H), tan($\beta$)), with sin($\theta$) = 0.35)

The expected exclusion contours as a function of (m(H), tan($\beta$)), with sin($\theta$) = 0.7)

The observed exclusion contours as a function of (m(H), tan($\beta$)), with sin($\theta$) = 0.7)

The expected exclusion contours as a function of (m(a), m(H)), with sin($\theta$) = 0.35)

The observed exclusion contours as a function of (m(a), m(H)), with sin($\theta$) = 0.35)

The expected exclusion contours as a function of (m(a), m(H)), with sin($\theta$) = 0.7)

The observed exclusion contours as a function of (m(a), m(H)), with sin($\theta$) = 0.7)

Expected lower limit on signal strength at 95% CL as a function of sin($\theta$), with m(a) = 200 GeV, m(H) = 600 GeV.

Observed lower limit on signal strength at 95% CL as a function of sin($\theta$), with m(a) = 200 GeV, m(H) = 600 GeV.

Expected lower limit on signal strength at 95% CL as a function of sin($\theta$), with m(a) = 350 GeV, m(H) = 1000 GeV.

Observed lower limit on signal strength at 95% CL as a function of sin($\theta$), with m(a) = 350 GeV, m(H) = 1000 GeV.

Observed lower limit on WIMP-nucleon cross section at 90% CL as a function of m(WIMP), assuming Higgs-portal scenario with Scalar WIMP.

Observed lower limit on WIMP-nucleon cross section at 90% CL as a function of m(WIMP), assuming Higgs-portal scenario with Majorana WIMP.

Observed lower limit on the spin-dependent WIMP–proton scattering cross-section.

Observed lower limit on the spin-independent WIMP–nucleon scattering cross-section.

Cutflow of unweighted and weighted events of $ZH$ signals in the electron channel.

Cutflow of unweighted and weighted events of $ZH$ signals in the muon channel.

Cutflow of unweighted and weighted events of DM signals (simplified DM axial-vector with m(med) = 900 GeV and m($\chi$) = 40 GeV, 2HDM+$a$ signal with m(A) = 600 GeV, m(a) = 400 GeV, tan($\beta$) = 1.0 and m($\chi$) = 10 GeV) in the electron channel.

Cutflow of unweighted and weighted events of DM signals (simplified DM axial-vector with m(med) = 900 GeV and m($\chi$) = 40 GeV, 2HDM+$a$ signal with m(A) = 600 GeV, m(a) = 400 GeV, tan($\beta$) = 1.0 and m($\chi$) = 10 GeV) in the muon channel.

The efficiency for simulated VBF events to pass each analysis cut.

The efficiency for simulated VH events to pass each analysis cut.

The efficiency for simulated ttH events to pass each analysis cut.

The fractional contribution of each production mode to a given analysis region around the Higgs boson peak, defined as 105 < mJ < 140 GeV. The fraction is given with respect to the total signal yield in the analysis region in question.

Signal acceptance times efficiency within the fiducial volume used in the fiducial region.

Signal acceptance times efficiency for the STXS volumes in the differential measurement. Along with the pTH requirements shown, |yH | < 2 is required. For events with pTH < 300 GeV, the acceptance times efficiency is less than 0.1 × 10−2.

Event yields and associated uncertainties after the global likelihood fit in the pT(H) > 450 GeV fiducial region. The total background yield can differ from the sum of the individual components due to rounding.

Event yields and associated uncertainties after the global likelihood fit of the differential regions. The total background yield can differ from the sum of the individual components due to rounding. The five STXS volumes are labeled pT0–pT4 corresponding to pTH < 300 GeV, 300 – 450 GeV, 450 – 650 GeV, 650 – 1000 GeV, and > 1000 GeV, respectively. The pT0 event yield is constrained to its SM value within the theoretical and experimental uncertainties and free parameters act independently on the remaining four volumes.

Pre-fit distribution of the reconstructed Higgs boson candidate $p_T^H$ for the dilepton $SR^{\geq 4j}_{\geq 4b}$ signal region. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations, except for the uncertainty in the $k({t\bar {t}+{\geq }1b})$ normalisation factor which is not defined pre-fit. The last bin includes the overflow.

Pre-fit distribution of the reconstructed Higgs boson candidate $p_T^H$ for the single-lepton resolved $SR^{\geq 6j}_{\geq 4b}$ signal region. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations, except for the uncertainty in the $k({t\bar {t}+{\geq }1b})$ normalisation factor which is not defined pre-fit. The last bin includes the overflow.

Pre-fit distribution of the reconstructed Higgs boson candidate $p_T^H$ for the single-lepton boosted ${{SR}_{{boosted}}}$ signal region. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations, except for the uncertainty in the $k({t\bar {t}+{\geq }1b})$ normalisation factor which is not defined pre-fit. The last bin includes the overflow.

Comparison of predicted and observed event yields in each of the control and signal regions in the dilepton channel after the fit to the data. The uncertainty band includes all uncertainties and their correlations.

Comparison of predicted and observed event yields in each of the control and signal regions in the single-lepton channels after the fit to the data. The uncertainty band includes all uncertainties and their correlations.

Comparison between data and prediction for the BDT discriminant in the dilepton SRs after the inclusive fit to the data for $0\le p_T^H<120$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.

Comparison between data and prediction for the BDT discriminant in the dilepton SRs after the inclusive fit to the data for $120\le p_T^H<200$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.

Comparison between data and prediction for the BDT discriminant in the dilepton SRs after the inclusive fit to the data for $200\le p_T^H<300$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.

Comparison between data and prediction for the BDT discriminant in the dilepton SRs after the inclusive fit to the data for $p_{{T}}^{H}\ge 300$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.

Comparison between data and prediction for the BDT discriminant in the single-lepton resolved SRs after the inclusive fit to the data for $0\le p_T^H<120$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.

Comparison between data and prediction for the BDT discriminant in the single-lepton resolved SRs after the inclusive fit to the data for $120\le p_T^H<200$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.

Comparison between data and prediction for the BDT discriminant in the single-lepton resolved SRs after the inclusive fit to the data for $200\le p_T^H<300$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.

Comparison between data and prediction for the BDT discriminant in the single-lepton resolved SRs after the inclusive fit to the data for $300\le p_T^H<450$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.

Comparison between data and prediction for the BDT discriminant in the single-lepton resolved SRs after the inclusive fit to the data for $p_{{T}}^{H}\ge 450$ GeV (yield only). The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.

Comparison between data and prediction for the BDT discriminant in the single-lepton boosted SRs after the inclusive fit to the data for $300\le p_T^H<450$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.

Comparison between data and prediction for the BDT discriminant in the single-lepton boosted SRs after the inclusive fit to the data for $p_{{T}}^{H}\ge 450$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.

Comparison between data and prediction for ${\Delta R^{{avg}}_{bb}}$ after the inclusive fit to the data in the single-lepton $CR^{5j}_{{\geq}4b\ lo}$ control region. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations. The first (last) bin includes the underflow (overflow).

Comparison between data and prediction for ${\Delta R^{{avg}}_{bb}}$ after the inclusive fit to the data in the single-lepton $CR^{5j}_{{\geq}4b\ hi}$ control region. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations. The first (last) bin includes the underflow (overflow).

Post-fit yields of signal ($S$) and total background ($B$) as a function of $\log (S/B)$, compared with data. Final-discriminant bins in all dilepton and single-lepton analysis regions are combined into bins of $\log (S/B)$, with the signal normalised to the SM prediction used for the computation of $\log (S/B)$. The signal is then shown normalised to the best-fit value and the SM prediction. The lower frame reports the ratio of data to background, and this is compared with the expected ${t\bar {t}H}$-signal-plus-background yield divided by the background-only yield for the best-fit signal strength (solid red line) and the SM prediction (dashed orange line).

Comparison between data and prediction for the reconstruction BDT score for the Higgs boson candidate identified using Higgs boson information, after the inclusive fit to the data in the dilepton resolved channel for $0\le p_T^H<120$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.

Comparison between data and prediction for the average $\Delta \eta $ between $b$-tagged jets, after the inclusive fit to the data in the dilepton resolved channel for $0\le p_T^H<120$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.

Comparison between data and prediction for the likelihood discriminant, after the inclusive fit to the data in the single-lepton resolved channel for $0\le p_T^H<120$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.

Comparison between data and prediction for the average $\Delta R$ for all possible combinations of $b$-tagged jet pairs, after the inclusive fit to the data in the single-lepton resolved channel for $0\le p_T^H<120$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.

Comparison between data and prediction for the DNN $P(H)$ output for the Higgs boson candidate after the inclusive fit to the data in the single-lepton boosted channel for $300\le p_T^H<450$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.

Comparison between data and prediction for the DNN $P(H)$ output for the Higgs boson candidate after the inclusive fit to the data in the single-lepton boosted channel for $p_{{T}}^{H}\ge 450$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.

Post-fit distribution of the reconstructed Higgs boson candidate mass for the dilepton $SR^{\geq 4j}_{\geq 4b}$ signal region. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations. The first (last) bin includes the underflow (overflow).

Post-fit distribution of the reconstructed Higgs boson candidate mass for the single-lepton resolved $SR^{\geq 6j}_{\geq 4b}$ signal region. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations. The first (last) bin includes the underflow (overflow).

Post-fit distribution of the reconstructed Higgs boson candidate mass for the single-lepton boosted ${{SR}_{{boosted}}}$ signal region. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations. The first (last) bin includes the underflow (overflow).

Fitted values of the ${t\bar {t}H}$ signal strength parameter in the individual channels and in the inclusive signal-strength measurement.

Ranking of the 20 nuisance parameters with the largest post-fit impact on $\mu $ in the fit. Nuisance parameters corresponding to statistical uncertainties in the simulated event samples are not included. The empty blue rectangles correspond to the pre-fit impact on $\mu $ and the filled blue ones to the post-fit impact on $\mu $, both referring to the upper scale. The impact of each nuisance parameter, $\Delta \mu $, is computed by comparing the nominal best-fit value of $\mu $ with the result of the fit when fixing the considered nuisance parameter to its best-fit value, $\hat{\theta }$, shifted by its pre-fit (post-fit) uncertainties $\pm \Delta \theta $ ($\pm \Delta \hat{\theta }$). The black points show the pulls of the nuisance parameters relative to their nominal values, $\theta _0$. These pulls and their relative post-fit errors, $\Delta \hat{\theta }/\Delta \theta $, refer to the lower scale. The `ljets' (`dilep') label refers to the single-lepton (dilepton) channel.

Pre-fit distribution of the number of jets in the dilepton $SR^{\geq 4j}_{\geq 4b}$ signal region. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the Standard Model expectation. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations, except the uncertainty in the $k({t\bar {t}+{\geq }1b})$ normalisation factor that is not defined pre-fit.

Pre-fit distribution of the number of jets in the single-lepton resolved $SR^{\geq 6j}_{\geq 4b}$ signal region. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the Standard Model expectation. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations, except the uncertainty in the $k({t\bar {t}+{\geq }1b})$ normalisation factor that is not defined pre-fit.

Pre-fit distribution of the number of jets in the single-lepton boosted ${{SR}_{{boosted}}}$ signal region. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the Standard Model expectation. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations, except the uncertainty in the $k({t\bar {t}+{\geq }1b})$ normalisation factor that is not defined pre-fit.

Post-fit distribution of the number of jets in the dilepton $SR^{\geq 4j}_{\geq 4b}$ signal region. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.

Post-fit distribution of the number of jets in the single-lepton resolved $SR^{\geq 6j}_{\geq 4b}$ signal region. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.

Post-fit distribution of the number of jets in the single-lepton boosted ${{SR}_{{boosted}}}$ signal region. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.

Post-fit distribution of the reconstructed Higgs boson candidate $p_T^H$ for the dilepton $SR^{\geq 4j}_{\geq 4b}$ signal region. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations. The last bin includes the overflow.

Post-fit distribution of the reconstructed Higgs boson candidate $p_T^H$ for the single-lepton resolved $SR^{\geq 6j}_{\geq 4b}$ signal region. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations. The last bin includes the overflow.

Post-fit distribution of the reconstructed Higgs boson candidate $p_T^H$ for the single-lepton boosted ${{SR}_{{boosted}}}$ signal region. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations. The last bin includes the overflow.

Signal-strength measurements in the individual STXS ${\hat{p}_{{T}}^{H}}$ bins, as well as the inclusive signal strength.

95% CL simplified template cross-section upper limits in the individual STXS ${\hat{p}_{{T}}^{H}}$ bins, as well as the inclusive limit. The observed limits are shown (solid black lines), together with the expected limits both in the background-only hypothesis (dotted black lines) and in the SM hypothesis (dotted red lines). In the case of the expected limits in the background-only hypothesis, one- and two-standard-deviation uncertainty bands are also shown. The hatched uncertainty bands correspond to the theory uncertainty in the fiducial cross-section prediction in each bin.

The ratios $S/B$ (black solid line, referring to the vertical axis on the left) and $S/\sqrt{B}$ (red dashed line, referring to the vertical axis on the right) for each category in the inclusive analysis in the dilepton channel (left) and in the single-lepton channels (right), where $S$ ($B$) is the number of selected signal (background) events predicted by the simulation and normalised to a luminosity of 139 fb$^{-1}$ .

Comparison between data and prediction for the $\Delta R$ between the Higgs candidate and the ${t\bar {t}}$ candidate system, after the inclusive fit to the data in the dilepton resolved channel for $0\le p_T^H<120$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.

Comparison between data and prediction for the number of $b$-tagged jet pairs with an invariant mass within 30 GeV of 125 GeV, after the inclusive fit to the data in the dilepton resolved channel for $0\le p_T^H<120$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.

Comparison between data and prediction for the reconstruction BDT score for the Higgs boson candidate identified using Higgs boson information, after the inclusive fit to the data in the single-lepton resolved channel for $0\le p_T^H<120$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.

Comparison between data and prediction for the $\Delta R$ between the two highest ${p_{{T}}}$ $b$-tagged jets, after the inclusive fit to the data in the single-lepton resolved channel for $0\le p_T^H<120$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.

Comparison between data and prediction for the sum of $b$-tagging discriminants of jets from Higgs, hadronic top and leptonic top candidates, after the inclusive fit to the data in the single-lepton boosted channel for $300\le p_T^H<450$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations. The first (last) bin includes the underflow (overflow).

Comparison between data and prediction for the sum of $b$-tagging discriminants of jets from Higgs, hadronic top and leptonic top candidates, after the inclusive fit to the data in the single-lepton boosted channel for $p_{{T}}^{H}\ge 450$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations. The first (last) bin includes the underflow (overflow).

Comparison between data and prediction for the hadronic top candidate invariant mass, after the inclusive fit to the data in the single-lepton boosted channel for $300\le p_T^H<450$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations. The first (last) bin includes the underflow (overflow).

Comparison between data and prediction for the hadronic top candidate invariant mass, after the inclusive fit to the data in the single-lepton boosted channel for $p_{{T}}^{H}\ge 450$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations. The first (last) bin includes the underflow (overflow).

Comparison between data and prediction for the fraction of the sum of $b$-tagging discriminants of all jets not associated to the Higgs or hadronic top candidates, after the inclusive fit to the data in the single-lepton boosted channel for $300\le p_T^H<450$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations. The first (last) bin includes the underflow (overflow).

Comparison between data and prediction for the fraction of the sum of $b$-tagging discriminants of all jets not associated to the Higgs or hadronic top candidates, after the inclusive fit to the data in the single-lepton boosted channel for $p_{{T}}^{H}\ge 450$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations. The first (last) bin includes the underflow (overflow).

Ranking of the 20 nuisance parameters with the largest post-fit impact on $\mu $ in the STXS fit for $0\le {\hat{p}_{{T}}^{H}}<120$ GeV. Nuisance parameters corresponding to statistical uncertainties in the simulated event samples are not included. The empty blue rectangles correspond to the pre-fit impact on $\mu $ and the filled blue ones to the post-fit impact on $\mu $, both referring to the upper scale. The impact of each nuisance parameter, $\Delta \mu $, is computed by comparing the nominal best-fit value of $\mu $ with the result of the fit when fixing the considered nuisance parameter to its best-fit value, $\hat{\theta }$, shifted by its pre-fit (post-fit) uncertainties $\pm \Delta \theta $ ($\pm \Delta \hat{\theta }$). The black points show the pulls of the nuisance parameters relative to their nominal values, $\theta _0$. These pulls and their relative post-fit errors, $\Delta \hat{\theta }/\Delta \theta $, refer to the lower scale. For experimental uncertainties that are decomposed into several independent sources, NP X corresponds to the X$^{th}$ nuisance parameter, ordered by their impact on $\mu $. The `ljets' (`dilep') label refers to the single-lepton (dilepton) channel.

Ranking of the 20 nuisance parameters with the largest post-fit impact on $\mu $ in the STXS fit for $120\le {\hat{p}_{{T}}^{H}}<200$ GeV. Nuisance parameters corresponding to statistical uncertainties in the simulated event samples are not included. The empty blue rectangles correspond to the pre-fit impact on $\mu $ and the filled blue ones to the post-fit impact on $\mu $, both referring to the upper scale. The impact of each nuisance parameter, $\Delta \mu $, is computed by comparing the nominal best-fit value of $\mu $ with the result of the fit when fixing the considered nuisance parameter to its best-fit value, $\hat{\theta }$, shifted by its pre-fit (post-fit) uncertainties $\pm \Delta \theta $ ($\pm \Delta \hat{\theta }$). The black points show the pulls of the nuisance parameters relative to their nominal values, $\theta _0$. These pulls and their relative post-fit errors, $\Delta \hat{\theta }/\Delta \theta $, refer to the lower scale. For experimental uncertainties that are decomposed into several independent sources, NP X corresponds to the X$^{th}$ nuisance parameter, ordered by their impact on $\mu $. The `ljets' (`dilep') label refers to the single-lepton (dilepton) channel.

Ranking of the 20 nuisance parameters with the largest post-fit impact on $\mu $ in the STXS fit for $200\le {\hat{p}_{{T}}^{H}}<300$ GeV. Nuisance parameters corresponding to statistical uncertainties in the simulated event samples are not included. The empty blue rectangles correspond to the pre-fit impact on $\mu $ and the filled blue ones to the post-fit impact on $\mu $, both referring to the upper scale. The impact of each nuisance parameter, $\Delta \mu $, is computed by comparing the nominal best-fit value of $\mu $ with the result of the fit when fixing the considered nuisance parameter to its best-fit value, $\hat{\theta }$, shifted by its pre-fit (post-fit) uncertainties $\pm \Delta \theta $ ($\pm \Delta \hat{\theta }$). The black points show the pulls of the nuisance parameters relative to their nominal values, $\theta _0$. These pulls and their relative post-fit errors, $\Delta \hat{\theta }/\Delta \theta $, refer to the lower scale. For experimental uncertainties that are decomposed into several independent sources, NP X corresponds to the X$^{th}$ nuisance parameter, ordered by their impact on $\mu $. The `ljets' (`dilep') label refers to the single-lepton (dilepton) channel.

Ranking of the 20 nuisance parameters with the largest post-fit impact on $\mu $ in the STXS fit for $300\le {\hat{p}_{{T}}^{H}}<450$ GeV. Nuisance parameters corresponding to statistical uncertainties in the simulated event samples are not included. The empty blue rectangles correspond to the pre-fit impact on $\mu $ and the filled blue ones to the post-fit impact on $\mu $, both referring to the upper scale. The impact of each nuisance parameter, $\Delta \mu $, is computed by comparing the nominal best-fit value of $\mu $ with the result of the fit when fixing the considered nuisance parameter to its best-fit value, $\hat{\theta }$, shifted by its pre-fit (post-fit) uncertainties $\pm \Delta \theta $ ($\pm \Delta \hat{\theta }$). The black points show the pulls of the nuisance parameters relative to their nominal values, $\theta _0$. These pulls and their relative post-fit errors, $\Delta \hat{\theta }/\Delta \theta $, refer to the lower scale. For experimental uncertainties that are decomposed into several independent sources, NP X corresponds to the X$^{th}$ nuisance parameter, ordered by their impact on $\mu $. The `ljets' (`dilep') label refers to the single-lepton (dilepton) channel.

Ranking of the 20 nuisance parameters with the largest post-fit impact on $\mu $ in the STXS fit for ${\hat{p}_{{T}}^{H}}\ge 450$ GeV. Nuisance parameters corresponding to statistical uncertainties in the simulated event samples are not included. The empty blue rectangles correspond to the pre-fit impact on $\mu $ and the filled blue ones to the post-fit impact on $\mu $, both referring to the upper scale. The impact of each nuisance parameter, $\Delta \mu $, is computed by comparing the nominal best-fit value of $\mu $ with the result of the fit when fixing the considered nuisance parameter to its best-fit value, $\hat{\theta }$, shifted by its pre-fit (post-fit) uncertainties $\pm \Delta \theta $ ($\pm \Delta \hat{\theta }$). The black points show the pulls of the nuisance parameters relative to their nominal values, $\theta _0$. These pulls and their relative post-fit errors, $\Delta \hat{\theta }/\Delta \theta $, refer to the lower scale. For experimental uncertainties that are decomposed into several independent sources, NP X corresponds to the X$^{th}$ nuisance parameter, ordered by their impact on $\mu $. The `ljets' (`dilep') label refers to the single-lepton (dilepton) channel.

95% confidence level upper limits on signal-strength measurements in the individual STXS ${\hat{p}_{{T}}^{H}}$ bins, as well as the inclusive signal-strength limit, after the fit used to extract multiple signal-strength parameters. The observed limits are shown (solid black lines), together with the expected limits both in the background-only hypothesis (dotted black lines) and in the SM hypothesis (dotted red lines). In the case of the expected limits in the background-only hypothesis, one- and two-standard-deviation uncertainty bands are also shown.

Post-fit correlation matrix (in percentages) between the $\mu $ values obtained in the STXS bins.

Performance of the Higgs boson reconstruction algorithms. For each row of `truth' ${\hat{p}_{{T}}^{H}}$, the matrix shows (in percentages) the fraction of Higgs boson candidates which are truth-matched to ${b\bar {b}}$ decays, with reconstructed $p_T^H$ in the various bins of the dilepton (left), single lepton resolved (middle) and boosted (right) channels.

Pre-fit event yields in the dilepton signal regions and control regions. All uncertainties are included except the $k({t\bar {t}+{\geq }1b})$ uncertainty that is not defined pre-fit. For the ${t\bar {t}H}$ signal, the pre-fit yield values correspond to the theoretical prediction and corresponding uncertainties. `Other sources' refers to s-channel, t-channel, $tW$, $tWZ$, $tZq$, $Z+$ jets and diboson events.

Post-fit event yields in the dilepton signal regions and control regions, after the inclusive fit in all channels. All uncertainties are included, taking into account correlations. For the ${t\bar {t}H}$ signal, the post-fit yield and uncertainties correspond to those in the inclusive signal-strength measurement. `Other sources' refers to s-channel, t-channel, $tW$, $tWZ$, $tZq$, $Z+$ jets and diboson events.

Pre-fit event yields in the single-lepton resolved and boosted signal regions and control regions. All uncertainties are included except the $k({t\bar {t}+{\geq }1b})$ uncertainty that is not defined pre-fit. For the ${t\bar {t}H}$ signal, the pre-fit yield values correspond to the theoretical prediction and corresponding uncertainties. `Other top sources' refers to s-channel, t-channel, $tWZ$ and $tZq$ events.

Post-fit event yields in the single-lepton resolved and boosted signal regions and control regions, after the inclusive fit in all channels. All uncertainties are included, taking into account correlations. For the ${t\bar {t}H}$ signal, the post-fit yield and uncertainties correspond to those in the inclusive signal-strength measurement. `Other top sources' refers to s-channel, t-channel, $tWZ$ and $tZq$ events.

Breakdown of the contributions to the uncertainties in $\mu$. The contributions from the different sources of uncertainty are evaluated after the fit. The $\Delta \mu $ values are obtained by repeating the fit after having fixed a certain set of nuisance parameters corresponding to a group of systematic uncertainties, and then evaluating $(\Delta \mu)^2$ by subtracting the resulting squared uncertainty of $\mu $ from its squared uncertainty found in the full fit. The same procedure is followed when quoting the effect of the ${t\bar {t}+{\geq }1b}$ normalisation. The total uncertainty is different from the sum in quadrature of the different components due to correlations between nuisance parameters existing in the fit.

Fraction (in percentages) of signal events, after SR and CR selections, originating from $b\bar {b}$, $WW$ and other remaining Higgs boson decay modes in the dilepton channel.

Fraction (in percentages) of signal events, after SR and CR selections, originating from $b\bar {b}$, $WW$ and other remaining Higgs boson decay modes in the single-lepton channels.

Predicted SM ${t\bar {t}H}$ cross-section in each of the five STXS ${\hat{p}_{{T}}^{H}}$ bins and signal acceptance times efficiency (including all event selection criteria) in each STXS bin as well as for the inclusive ${\hat{p}_{{T}}^{H}}$ range.

Number of expected signal events before the fit, after each selection requirement applied to enter the dilepton channel $SR^{\geq 4j}_{\geq 4b}$ region. All ${t\bar {t}H}$ signal events are included, regardless of the $H$ or ${t\bar {t}H}$ decay mode. All object corrections are applied, except for the initial number of events which is calculated using the NLO QCD+EW theoretical prediction. All quoted numbers are rounded to unity. More details on the selection criteria can be found in the text.

Number of expected signal events before the fit, after each selection requirement applied to enter the single-lepton channel resolved $SR^{\geq 6j}_{\geq 4b}$ region. All ${t\bar {t}H}$ signal events are included, regardless of the $H$ or ${t\bar {t}H}$ decay mode. All object corrections are applied, except for the initial number of events which is calculated using the NLO QCD+EW theoretical prediction. All quoted numbers are rounded to unity. More details on the selection criteria can be found in the text.

Number of expected signal events before the fit, after each selection requirement applied to enter the single-lepton channel boosted $SR_{boosted}$ region. All ${t\bar {t}H}$ signal events are included, regardless of the $H$ or ${t\bar {t}H}$ decay mode. All object corrections are applied, except for the initial number of events which is calculated using the NLO QCD+EW theoretical prediction. All quoted numbers are rounded to unity. More details on the selection criteria can be found in the text.

Correlation coefficients $\rho_{i,j}$ for the statistical and systematic uncertainties between the $i$-th and $j$-th bin of the differential $A_E$ measurement as a function of the jet scattering angle $\theta_j$

The effects on the energy asymmetry of $1\sigma$ variations in its influencing nuisance parameters for the three $\theta_j$ bins. These are extracted from the samples of the posterior distribution with $\sigma_i^{(j)} = c_{ij}/\sqrt{c_{jj}}$ being the estimated shift of bin $i$ in conjunction with a shift $\Delta\theta_j$ of nuisance parameter $j$. The data statistical (Data stat.) uncertainty is obtained from running the unfolding with all nuisance parameters being fixed to their post-marginalised values, the MC statistical uncertainty on the response matrix ($t\bar{t}$ response MC stat.) is evaluated using a bootstrapping method from the covariance matrix of the ensemble of repeated unfolding results with varied response matrices. The $\gamma$ variations denote the statistical uncertainties of the background predictions in the corresponding bin of the $\Delta E$ vs $\theta_{j}$ distribution. The numbers appended to the $W$+jets PDF variations denote the corresponding NNPDF3.0 PDF sets.

The effects on the energy asymmetry of $1\sigma$ variations in its influencing nuisance parameters for the three $\theta_j$ bins. These are extracted from the samples of the posterior distribution with $\sigma_i^{(j)} = c_{ij}/\sqrt{c_{jj}}$ being the estimated shift of bin $i$ in conjunction with a shift $\Delta\theta_j$ of nuisance parameter $j$. The data statistical (Data stat.) uncertainty is obtained from running the unfolding with all nuisance parameters being fixed to their post-marginalised values, the MC statistical uncertainty on the response matrix ($t\bar{t}$ response MC stat.) is evaluated using a bootstrapping method from the covariance matrix of the ensemble of repeated unfolding results with varied response matrices. The $\gamma$ variations denote the statistical uncertainties of the background predictions in the corresponding bin of the $\Delta E$ vs $\theta_{j}$ distribution. The numbers appended to the $W$+jets PDF variations denote the corresponding NNPDF3.0 PDF sets.

Covariances $c_{ij}$ for the highest ranked systematic uncertainties in the energy asymmetry measurement differential in $\theta_j$.

Covariances $c_{ij}$ for the highest ranked systematic uncertainties in the energy asymmetry measurement differential in $\theta_j$.

Definition of the fiducial phase space with lepton candidate ($\ell$), hadronic top candidate ($j_h$), leptonic top candidate ($j_l$) and associated jet candidate ($j_a$).

Definition of the fiducial phase space with lepton candidate ($\ell$), hadronic top candidate ($j_h$), leptonic top candidate ($j_l$) and associated jet candidate ($j_a$).

Bounds on individual Wilson coefficients $C($TeV$/\Lambda)^2$ from the energy asymmetry, obtained from a combined fit to its values in all three $\theta_j$ bins.

Bounds on individual Wilson coefficients $C($TeV$/\Lambda)^2$ from the energy asymmetry, obtained from a combined fit to its values in all three $\theta_j$ bins.

Upper limits on $\mathcal{B}(H\rightarrow aa\rightarrow bb\mu\mu)$ at 95% CL including the BDT cut as a function of the signal mass.

Upper limits on $\mathcal{B}(H\rightarrow aa\rightarrow bb\mu\mu)$ at 95% CL without the BDT cut as a function of the signal mass.

The number of events when applying each cut in the analysis for $m_a$ = 16 GeV. The first row shows the approximate total number of events scaled to the theoretical signal cross-section and luminosity of the full Run 2 dataset, assuming $ \mathcal{B}(H\rightarrow aa\rightarrow bb\mu\mu)$ = 0.16%.

The number of events when applying each cut in the analysis for $m_a$ = 20 GeV. The first row shows the approximate total number of events scaled to the theoretical signal cross-section and luminosity of the full Run 2 dataset, assuming $ \mathcal{B}(H\rightarrow aa\rightarrow bb\mu\mu)$ = 0.16%.

The number of events when applying each cut in the analysis for $m_a$ = 30 GeV. The first row shows the approximate total number of events scaled to the theoretical signal cross-section and luminosity of the full Run 2 dataset, assuming $ \mathcal{B}(H\rightarrow aa\rightarrow bb\mu\mu)$ = 0.16%.

The number of events when applying each cut in the analysis for $m_a$ = 40 GeV. The first row shows the approximate total number of events scaled to the theoretical signal cross-section and luminosity of the full Run 2 dataset, assuming $ \mathcal{B}(H\rightarrow aa\rightarrow bb\mu\mu)$ = 0.16%.

The number of events when applying each cut in the analysis for $m_a$ = 50 GeV. The first row shows the approximate total number of events scaled to the theoretical signal cross-section and luminosity of the full Run 2 dataset, assuming $ \mathcal{B}(H\rightarrow aa\rightarrow bb\mu\mu)$ = 0.16%.

The number of events when applying each cut in the analysis for $m_a$ = 60 GeV. The first row shows the approximate total number of events scaled to the theoretical signal cross-section and luminosity of the full Run 2 dataset, assuming $ \mathcal{B}(H\rightarrow aa\rightarrow bb\mu\mu)$ = 0.16%.

Post-fit event yields in the signal and control regions obtained from a scan over $\epsilon_{VV}$ exploiting both shape and rate information. The quoted uncertainties include the theoretical and experimental systematic sources and those due to sample statistics. The fit constrains the total expected yield to the observed yield. The diboson background is split into $W W$ and non-$W W$ contributions.

Best-fit values and their uncertainties as obtained from the shape-only and shape-plus-rate likelihood fits to the Asimov dataset and to ATLAS data. Results of both shape-only and shape+rate fits for $a_L$ and $a_T$ are shown. Results of fits to one parameter with the other one fixed or profiled are presented.

Best-fit values and their uncertainties as obtained from the shape-only and shape-plus-rate likelihood fits to the Asimov dataset and to ATLAS data. Results of both shape-only and shape+rate fits for $\epsilon_{VV}$ and $\kappa_{VV}$ are shown. Results of fits to one parameter with the other one fixed or profiled are presented.

The contributions of the leading individual systematic uncertainties together with the data statistical uncertainties, in the one dimensional fit for the pseudo-observables $\kappa_{VV}$ (a) and $\epsilon_{VV}$ (b) for electroweak-boson polarisation in the VBF $H\to WW$ channel. Both shape and rate informations are exploited in the fit. The theoretical and experimental uncertainties are subdivided further into categories.

The contributions of the leading individual systematic uncertainties together with the data statistical uncertainties, in the one dimensional fit for the pseudo-observables $\kappa_{VV}$ (a) and $\epsilon_{VV}$ (b) for electroweak-boson polarisation in the VBF $H\to WW$ channel. Both shape and rate informations are exploited in the fit. The theoretical and experimental uncertainties are subdivided further into categories.

Post-fit distribution of the BDT response observable presented in the four $|\Delta \eta jj|$ categories of the ggF +2 jets signal region, with signal and background yields fixed from the fit for $\mu^{\text{ggF+2jets}}$. The distributions of the ggF + 2 jets and VBF processes are overlaid with their respective contributions multiplied by 50.

The weighted $\Delta \Phi_{jj}$ post-fit distribution in the ggF +2 jets signal region, with signal and background yields fixed from the fit to $\tan \alpha$ using shape and rate information.

Expected and observed likelihood curves for scans over $\tan \alpha$ where only the shape is taken into account in the fit, $\mu_{VBF}$ is fixed.

Expected and observed likelihood curves for scans over $\tan \alpha$ where both shape and normalisation are taken into account in the fit, $\mu_{VBF}$ is fixed.

68% and 95% CL two-dimensional likelihood contours of the CP-even and CP-odd coupling parameters $K_{gg} \cos(\alpha)$ and $K_{gg} \sin(\alpha)$. The minima are represented by black stars, while the SM value is shown as a red star.

The weighted $\Delta \Phi jj$ distribution in the VBF signal region, with signal and background yields fixed from the fit for $\epsilon_{VV}$ using shape and rate information.

Likelihood scans over the transversally polarised couplings. The fit is using shape-only information. All relevant experimental and modelling systematic uncertainties are considered in the fit.

Likelihood scans over the transversally polarised couplings. The fit is using shape + rate information. All relevant experimental and modelling systematic uncertainties are considered in the fit.

Likelihood scans over the longitudinally polarised couplings. The fit is using shape + rate information. All relevant experimental and modelling systematic uncertainties are considered in the fit.

Likelihood scans over $\kappa_{VV}$ with the $\epsilon_{VV}$ profiled. The fit is performed using both shape and rate information. All relevant experimental and theoretical systematic uncertainties are considered in the fit.

Likelihood scans over $\epsilon_{VV}$ with the $\kappa_{VV}$ profiled. The fit is performed using both shape and rate information. All relevant experimental and theoretical systematic uncertainties are considered in the fit.

The contributions of the leading individual systematic uncertainties together with the data statistical uncertainties, in the one dimensional fit for electroweak-boson polarisation in the VBF $H\to WW$ channel, using (aL, aT) parametrisation. Both shape and rate informations are exploited in the fit. The theoretical and experimental uncertainties are subdivided further into categories.

The contributions of the leading individual systematic uncertainties together with the data statistical uncertainties, in the one dimensional fit for electroweak-boson polarisation in the VBF $H\to WW$ channel, using (aL, aT) parametrisation.. Both shape and rate informations are exploited in the fit. The theoretical and experimental uncertainties are subdivided further into categories.

Post-fit $m_\text{T}(\gamma, E_\text{T}^\text{miss})$ distribution in the inclusive signal region for the dark-photon search with the 125 GeV mass $\mathcal{B}(H \to \gamma \gamma_\text{d})$ signal normalization set to zero. A $H \to \gamma \gamma_\text{d}$ decay signal is shown for two different mass hypotheses, 125 GeV and 500 GeV, and scaled to a $\mathcal{B}(H \to \gamma \gamma_\text{d})$ of 2% and 1%, respectively. Events with $m_\text{T}(\gamma, E_\text{T}^\text{miss})$ larger than the rightmost bin boundary are added to that bin.

The 95% CL upper limit on the Higgs boson production cross-section times branching ratio to $\gamma \gamma_\text{d}$ is shown for different VBF-produced scalar-mediator-mass hypotheses in the NWA. The theoretically predicted cross-section of a Higgs boson produced via VBF and with the $\mathcal{B}(H \to \gamma \gamma_\text{d}) =$ 5% is superimposed on the $\pm 1\sigma$ and $\pm 2\sigma$ NNLO QCD + NLO EW uncertainty band of the expected production cross-section limit.

Post-fit $m_\text{jj}$ distribution in the inclusive signal region. The Higgs boson invisible decay signal is scaled to a $\mathcal{B}_\text{inv}$ of 37%. Events with $m_\text{jj}$ larger than the rightmost bin boundary are added to that bin.

Post-fit $m_\text{jj}$ distribution in the one-lepton control region $W_{\ell \nu}^\gamma$ CR. Events with $m_\text{jj}$ larger than the rightmost bin boundary are added to that bin.

Post-fit $m_\text{T}$ distribution in the one lepton control region. Events with $m_\text{T}$ larger than the rightmost bin boundary are added to that bin.

Post-fit photon centrality distribution in the zero lepton signal plus control region with the $\mathcal{B}_\text{inv}$ signal normalization set to zero in the fit.

Post-fit photon $E_\text{T}$ distribution in the zero lepton signal region with the $\mathcal{B}_\text{inv}$ signal normalization set to zero in the fit.

Post-fit photon centrality distribution in the zero lepton signal plus control region resulting from the fit to the $m_\text{jj}$ distribution for EW $Z \gamma + \text{jets}$. The post-fit uncertainties include statistical, experimental, and theory contributions.

Post-fit photon $E_\text{T}$ distribution in the zero lepton signal region resulting from the fit to the $m_\text{jj}$ distribution for EW $Z \gamma + \text{jets}$. The post-fit uncertainties include statistical, experimental, and theory contributions.

Post-fit DNN output score distribution in the one lepton control region.

Yields for the EW $Z \gamma + \text{jets}$ process are shown after each selection along with relative and absolute signal acceptance efficiencies.

Yields for the 125 GeV Higgs boson with $\mathcal{B}_\text{inv.} =$ 1 signal produced by the vector boson fusion process in association with a final state photon are shown after each selection along with relative and absolute signal acceptance efficiencies.

Yields for the 125 GeV Higgs boson with $\mathcal{B}(H \to \gamma \gamma_\text{d}) =$ 1 signal produced by the vector boson fusion process are shown after each selection along with relative and absolute signal acceptance efficiencies.

Expected +- 1 sigma 95% CL exclusion limit for the Zprime-2HDM model.

Expected +- 2 sigma 95% CL exclusion limit for the Zprime-2HDM model.

Observed 95% CL exclusion limit for the 2HDM+a model ggF production.

Expected 95% CL exclusion limit for the 2HDM+a model ggF production.

Expected +- 1 sigma 95% CL exclusion limit for the 2HDM+a model ggF production.

Expected +- 2 sigma 95% CL exclusion limit for the 2HDM+a model ggF production.

Observed 95% CL exclusion limit for the 2HDM+a model bbA production.

Expected 95% CL exclusion limit for the 2HDM+a model bbA production.

Expected +- 1 sigma 95% CL exclusion limit for the 2HDM+a model bbA production.

Expected +- 2 sigma 95% CL exclusion limit for the 2HDM+a model bbA production.

Observed 95% CL exclusion limit for the Zprime-2HDM model with the benchmark used in arXiv:1707.01302.

Expected 95% CL exclusion limit for the Zprime-2HDM model with the benchmark used in arXiv:1707.01302.

Expected +- 1 sigma 95% CL exclusion limit for the Zprime-2HDM model with the benchmark used in arXiv:1707.01302.

Expected +- 2 sigma 95% CL exclusion limit for the Zprime-2HDM model with the benchmark used in arXiv:1707.01302.

Expected and observed upper limits at 95% CL on cross-section for Zprime-2HDM model.

Expected and observed upper limits at 95% CL on cross-section for ggF producton in the 2HDM+a model.

Expected and observed upper limits at 95% CL on cross-section for bbA producton in the 2HDM+a model.

Model-independent upper limits on the visible cross-section $σ_{vis, $h(\bar{b})+DM} ≡ σ_{h+DM} \times B(h \to b\bar{b}) \times \mathcal{A} \times \epsilon$ in the different signal regions.

Theory cross-section for Zprime-2HDM model.

Theory cross-section for bbA production in the 2HDM+a model.

Theory cross-section for ggF production in the 2HDM+a model.

Distribution of Higgs boson candidate mass in 2b region with MET=150-200 GeV.

Distribution of Higgs boson candidate mass in 2b region with MET=200-350 GeV.

Distribution of Higgs boson candidate mass in 2b region with MET=350-500 GeV.

Distribution of Higgs boson candidate mass in 2b region with MET=500-750 GeV.

Distribution of Higgs boson candidate mass in 2b region with MET > 750 GeV.

Distribution of Higgs boson candidate mass in 3b region with MET=150-200 GeV.

Distribution of Higgs boson candidate mass in 3b region with MET=200-350 GeV.

Distribution of Higgs boson candidate mass in 3b region with MET=350-500 GeV.

Distribution of Higgs boson candidate mass in 3b region with MET > 500 GeV.

Yields in 1-lepton control region.

Yields in 2-lepton control region.

MET distribution in 2b region of the 0-lepton channel.

MET distribution in 3b region of the 0-lepton channel.

Expected signal yields after certain selection cuts in 2b region with MET=150-200 GeV.

Expected signal yields after certain selection cuts in 2b region with MET=200-350 GeV.

Expected signal yields after certain selection cuts in 2b region with MET=350-500 GeV.

Expected signal yields after certain selection cuts in 2b region with MET=500-750 GeV.

Expected signal yields after certain selection cuts in 2b region with MET > 750 GeV.

Expected signal yields after certain selection cuts in 3b region with MET=150-200 GeV.

Expected signal yields after certain selection cuts in 3b region with MET=200-350 GeV.

Expected signal yields after certain selection cuts in 3b region with MET=350-500 GeV.

Expected signal yields after certain selection cuts in 3b region with MET > 500 GeV.

Acceptance times efficiency for bbA production in the 2HDM+a model - 2b region with MET=150-200 GeV.

Acceptance times efficiency for bbA production in the 2HDM+a model - 2b region with MET=200-350 GeV.

Acceptance times efficiency for bbA production in the 2HDM+a model - 2b region with MET=350-500 GeV.

Acceptance times efficiency for bbA production in the 2HDM+a model - 2b region with MET=500-750 GeV.

Acceptance times efficiency for bbA production in the 2HDM+a model - 2b region with MET > 750 GeV.

Acceptance times efficiency for bbA production in the 2HDM+a model - 3b region with MET=150-200 GeV.

Acceptance times efficiency for bbA production in the 2HDM+a model - 3b region with MET=200-350 GeV.

Acceptance times efficiency for bbA production in the 2HDM+a model - 3b region with MET=350-500 GeV.

Acceptance times efficiency for bbA production in the 2HDM+a model - 3b region with MET>500 GeV.

Acceptance times efficiency for ggF production in the 2HDM+a model - 2b region with MET=150-200 GeV.

Acceptance times efficiency for ggF production in the 2HDM+a model - 2b region with MET=200-350 GeV.

Acceptance times efficiency for ggF production in the 2HDM+a model - 2b region with MET=350-500 GeV.

Acceptance times efficiency for ggF production in the 2HDM+a model - 2b region with MET=500-750 GeV.

Acceptance times efficiency for ggF production in the 2HDM+a model - 2b region with MET > 750 GeV.

Acceptance times efficiency for ggF production in the 2HDM+a model - 3b region with MET=150-200 GeV.

Acceptance times efficiency for ggF production in the 2HDM+a model - 3b region with MET=200-350 GeV.

Acceptance times efficiency for ggF production in the 2HDM+a model - 3b region with MET=350-500 GeV.

Acceptance times efficiency for ggF production in the 2HDM+a model - 3b region with MET > 500 GeV.

Acceptance times efficiency for ggF production in the Zprime-2HDM model - 2b region with MET=150-200 GeV.

Acceptance times efficiency for ggF production in the Zprime-2HDM model - 2b region with MET=200-350 GeV.

Acceptance times efficiency for ggF production in the Zprime-2HDM model - 2b region with MET=350-500 GeV.

Acceptance times efficiency for ggF production in the Zprime-2HDM model - 2b region with MET=500-750 GeV.

Acceptance times efficiency for ggF production in the Zprime-2HDM model - 2b region with MET > 750 GeV.

Acceptance times efficiency for ggF production in the Zprime-2HDM model - 3b region with MET=150-200 GeV.

Acceptance times efficiency for ggF production in the Zprime-2HDM model - 3b region with MET=200-350 GeV.

Acceptance times efficiency for ggF production in the Zprime-2HDM model - 3b region with MET=350-500 GeV.

Acceptance times efficiency for ggF production in the Zprime-2HDM model - 3b region with MET > 500 GeV.

Transverse profile for 70 GeV < pT < 100 GeV.

Longitudinal profile for pT > 100 GeV.

Transverse profile for pT > 100 GeV.

Average longitudinal profile

Transverse profile for pT > 100 GeV.

Fitted event-level b-tagging selection efficiency as a function of the dijet invariant mass. The uncertainties are evaluated by propagating the uncertainties on the fit parameters to the fitted efficiency.

Distributions of $s_{\text{T}}$ in the single-tau one-bin SR. The stacked histograms show the various SM background contributions. The hatched band indicates the total statistical and systematic uncertainty of the SM background. The $t\bar{t}$ (2 real $\tau$) and $t\bar{t}$ (1 real $\tau$) as well as the single-top background contributions are scaled with the normalization factors obtained from the background-only fit. Minor backgrounds are grouped together and denoted as 'Other'. This includes $t\bar{t}$-fake, single top, and other top (di-tau channel) or $t\bar{t}$-fake, $t\bar{t}+H$, multiboson, and other top (single-tau channel). The overlaid dotted lines show the additional contributions for signal scenarios close to the expected exclusion contour with the particle type and the mass and $\beta$ parameters for the simplified models indicated in the legend. For the leptoquark signal model the shapes of the distributions for $\text{LQ}_{3}^{\text{d}}$ and $\text{LQ}_{3}^{\text{v}}$ (not shown) are similar to that of $\text{LQ}_{3}^{\text{u}}$. The rightmost bin includes the overflow.

Distributions of $m_{\text{T}}(\tau)$ in the single-tau one-bin SR. The stacked histograms show the various SM background contributions. The hatched band indicates the total statistical and systematic uncertainty of the SM background. The $t\bar{t}$ (2 real $\tau$) and $t\bar{t}$ (1 real $\tau$) as well as the single-top background contributions are scaled with the normalization factors obtained from the background-only fit. Minor backgrounds are grouped together and denoted as 'Other'. This includes $t\bar{t}$-fake, single top, and other top (di-tau channel) or $t\bar{t}$-fake, $t\bar{t}+H$, multiboson, and other top (single-tau channel). The overlaid dotted lines show the additional contributions for signal scenarios close to the expected exclusion contour with the particle type and the mass and $\beta$ parameters for the simplified models indicated in the legend. For the leptoquark signal model the shapes of the distributions for $\text{LQ}_{3}^{\text{d}}$ and $\text{LQ}_{3}^{\text{v}}$ (not shown) are similar to that of $\text{LQ}_{3}^{\text{u}}$. The rightmost bin includes the overflow.

Distributions of $\Sigma m_{\text{T}}(b_{1,2})$ in the single-tau $p_{\text{T}}(\tau)$-binned SR. The stacked histograms show the various SM background contributions. The hatched band indicates the total statistical and systematic uncertainty of the SM background. The $t\bar{t}$ (2 real $\tau$) and $t\bar{t}$ (1 real $\tau$) as well as the single-top background contributions are scaled with the normalization factors obtained from the background-only fit. Minor backgrounds are grouped together and denoted as 'Other'. This includes $t\bar{t}$-fake, single top, and other top (di-tau channel) or $t\bar{t}$-fake, $t\bar{t}+H$, multiboson, and other top (single-tau channel). The overlaid dotted lines show the additional contributions for signal scenarios close to the expected exclusion contour with the particle type and the mass and $\beta$ parameters for the simplified models indicated in the legend. For the leptoquark signal model the shapes of the distributions for $\text{LQ}_{3}^{\text{d}}$ and $\text{LQ}_{3}^{\text{v}}$ (not shown) are similar to that of $\text{LQ}_{3}^{\text{u}}$. The rightmost bin includes the overflow.

Distributions of $p_{\text{T}}(\tau)$ in the single-tau $p_{\text{T}}(\tau)$-binned SR. The stacked histograms show the various SM background contributions. The hatched band indicates the total statistical and systematic uncertainty of the SM background. The $t\bar{t}$ (2 real $\tau$) and $t\bar{t}$ (1 real $\tau$) as well as the single-top background contributions are scaled with the normalization factors obtained from the background-only fit. Minor backgrounds are grouped together and denoted as 'Other'. This includes $t\bar{t}$-fake, single top, and other top (di-tau channel) or $t\bar{t}$-fake, $t\bar{t}+H$, multiboson, and other top (single-tau channel). The overlaid dotted lines show the additional contributions for signal scenarios close to the expected exclusion contour with the particle type and the mass and $\beta$ parameters for the simplified models indicated in the legend. For the leptoquark signal model the shapes of the distributions for $\text{LQ}_{3}^{\text{d}}$ and $\text{LQ}_{3}^{\text{v}}$ (not shown) are similar to that of $\text{LQ}_{3}^{\text{u}}$. The rightmost bin includes the overflow.

Observed event yields in data ('Observed') and expected event yields for SM background processes obtained from the background-only fit ('Total bkg.' and rows below) in the signal regions of the di-tau and single-tau channels. The quoted uncertainties include both the statistical and systematic uncertainties and are truncated at zero yield. By construction, no $t\bar{t}$ (2 real $\tau$) events can pass the selections in the single-tau channel. As the individual uncertainties are correlated, they do not add in quadrature to equal the total background uncertainty.

From left to right: upper limits at the 95% confidence level (CL) on the visible cross section ($\sigma_\text{vis}$) and on the number of signal events ($S_{\text{obs}}^{95}$). The third column ($S_{\text{exp}}^{95}$) shows the upper limit at the 95% CL on the number of signal events, given the expected number (and $\pm 1\,\sigma$ excursions on the expectation) of background events. The last two columns indicate the confidence level observed for the background-only hypothesis ($\text{CL}_{b}$), the discovery $p$-value ($p(s=0)$) and the significance ($Z$). In the di-tau SR, where fewer events are observed than predicted by the fitted background estimate, the $p$-value is capped at 0.5.

Expected and observed exclusion contours at the 95% confidence level for the vector third-generation leptoquark signal model, as a function of the mass $m(\text{LQ}_{3}^{\text{v}})$ and the branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ into a quark and a charged lepton. The plot shows the exclusion contour for the minimal-coupling scenario. The limits are derived from the binned single-tau signal region.

Expected and observed exclusion contours at the 95% confidence level for the vector third-generation leptoquark signal model, as a function of the mass $m(\text{LQ}_{3}^{\text{v}})$ and the branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ into a quark and a charged lepton. The plot shows the exclusion contour for the minimal-coupling scenario. The limits are derived from the binned single-tau signal region.

Expected and observed exclusion contours at the 95% confidence level for the vector third-generation leptoquark signal model, as a function of the mass $m(\text{LQ}_{3}^{\text{v}})$ and the branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ into a quark and a charged lepton. The plot shows the exclusion contour for vector leptoquarks with additional gauge couplings. The limits are derived from the binned single-tau signal region.

Expected and observed exclusion contours at the 95% confidence level for the vector third-generation leptoquark signal model, as a function of the mass $m(\text{LQ}_{3}^{\text{v}})$ and the branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ into a quark and a charged lepton. The plot shows the exclusion contour for vector leptoquarks with additional gauge couplings. The limits are derived from the binned single-tau signal region.

Exclusion contours at the 95% confidence level for the stop-stau signal model as a function of the masses of the top squark $m(\tilde{t}_{1})$ and of the tau slepton $m(\tilde{\tau}_{1})$. Expected and observed limits are shown for the present search in comparison to observed limits from previous ATLAS analyses based on data from Run-1 of the LHC at $\sqrt{s} = 8$ TeV [Eur. Phys. J. C 76 (2016)] and on a partial dataset from Run 2 at $\sqrt{s} = 13$ TeV [Phys. Rev. D 98 (2018) 032008]. The green band indicates the limit on the mass of the tau slepton (for a massless LSP) from the LEP experiments.

Exclusion contours at the 95% confidence level for the stop-stau signal model as a function of the masses of the top squark $m(\tilde{t}_{1})$ and of the tau slepton $m(\tilde{\tau}_{1})$. Expected and observed limits are shown for the present search in comparison to observed limits from previous ATLAS analyses based on data from Run-1 of the LHC at $\sqrt{s} = 8$ TeV [Eur. Phys. J. C 76 (2016)] and on a partial dataset from Run 2 at $\sqrt{s} = 13$ TeV [Phys. Rev. D 98 (2018) 032008]. The green band indicates the limit on the mass of the tau slepton (for a massless LSP) from the LEP experiments.

Expected and observed exclusion contours at the 95% confidence level for the scalar third-generation leptoquark signal model, as a function of the mass $m(\text{LQ}_{3}^{\text{u}})$ and the branching fraction $B(\text{LQ}_{3}^{\text{u}} \rightarrow q\ell)$ into a quark and a charged lepton. The plot shows the exclusion contour for up-type leptoquarks $\text{LQ}_{3}^{\text{u}})$ with charge $+2/3e$. The limits are derived from the binned single-tau signal region. Shown in gray for comparison are the observed exclusion-limit contours from the previous ATLAS publication that targets the same leptoquark models but is based on a subset of the Run-2 data [JHEP 06 (2019) 144]. In this previous publication five different analyses are considered that target not only the final state studied here but also the final states that correspond to a branching fraction $B(\text{LQ}_{3}^{\text{u}} \rightarrow q\ell)$ of 0 or 1, leading to the concave shapes of the gray exclusion contours.

Expected and observed exclusion contours at the 95% confidence level for the scalar third-generation leptoquark signal model, as a function of the mass $m(\text{LQ}_{3}^{\text{u}})$ and the branching fraction $B(\text{LQ}_{3}^{\text{u}} \rightarrow q\ell)$ into a quark and a charged lepton. The plot shows the exclusion contour for up-type leptoquarks $\text{LQ}_{3}^{\text{u}})$ with charge $+2/3e$. The limits are derived from the binned single-tau signal region. Shown in gray for comparison are the observed exclusion-limit contours from the previous ATLAS publication that targets the same leptoquark models but is based on a subset of the Run-2 data [JHEP 06 (2019) 144]. In this previous publication five different analyses are considered that target not only the final state studied here but also the final states that correspond to a branching fraction $B(\text{LQ}_{3}^{\text{u}} \rightarrow q\ell)$ of 0 or 1, leading to the concave shapes of the gray exclusion contours.

Expected and observed exclusion contours at the 95% confidence level for the scalar third-generation leptoquark signal model, as a function of the mass $m(\text{LQ}_{3}^{\text{d}})$ and the branching fraction $B(\text{LQ}_{3}^{\text{d}} \rightarrow q\ell)$ into a quark and a charged lepton. The plot shows the exclusion contour for down-type leptoquarks $\text{LQ}_{3}^{\text{d}})$ with charge $-1/3e$. The limits are derived from the binned single-tau signal region. Shown in gray for comparison are the observed exclusion-limit contours from the previous ATLAS publication that targets the same leptoquark models but is based on a subset of the Run-2 data [JHEP 06 (2019) 144]. In this previous publication five different analyses are considered that target not only the final state studied here but also the final states that correspond to a branching fraction $B(\text{LQ}_{3}^{\text{d}} \rightarrow q\ell)$ of 0 or 1, leading to the concave shapes of the gray exclusion contours.

Expected and observed exclusion contours at the 95% confidence level for the scalar third-generation leptoquark signal model, as a function of the mass $m(\text{LQ}_{3}^{\text{d}})$ and the branching fraction $B(\text{LQ}_{3}^{\text{d}} \rightarrow q\ell)$ into a quark and a charged lepton. The plot shows the exclusion contour for down-type leptoquarks $\text{LQ}_{3}^{\text{d}})$ with charge $-1/3e$. The limits are derived from the binned single-tau signal region. Shown in gray for comparison are the observed exclusion-limit contours from the previous ATLAS publication that targets the same leptoquark models but is based on a subset of the Run-2 data [JHEP 06 (2019) 144]. In this previous publication five different analyses are considered that target not only the final state studied here but also the final states that correspond to a branching fraction $B(\text{LQ}_{3}^{\text{d}} \rightarrow q\ell)$ of 0 or 1, leading to the concave shapes of the gray exclusion contours.

Upper limits on the signal cross section at the 95 % confidence level for the stop-stau signal model.

Upper limits on the signal cross section at the 95 % confidence level for the scalar third-generation leptoquark signal model with up-type leptoquarks.

Upper limits on the signal cross section at the 95 % confidence level for the scalar third-generation leptoquark signal model with down-type leptoquarks.

Upper limits on the signal cross section at the 95 % confidence level for the vector third-generation leptoquark signal model with minimal coupling (MC).

Upper limits on the signal cross section at the 95 % confidence level for the vector third-generation leptoquark signal model with additional gauge couplings (YM).

Acceptance of the one-bin signal region of the single-tau channel for pair production of up-type leptoquarks $\text{LQ}_{3}^{\text{u}}$.

Efficiency of the one-bin signal region of the single-tau channel for pair production of up-type leptoquarks $\text{LQ}_{3}^{\text{u}}$. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{u}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.

Acceptance of the first bin of the multi-bin signal region (50 GeV $< p_{\text{T}}(\tau) <$ 100 GeV) of the single-tau channel for pair production of up-type leptoquarks $\text{LQ}_{3}^{\text{u}}$.

Efficiency of the first bin of the multi-bin signal region (50 GeV $< p_{\text{T}}(\tau) <$ 100 GeV) of the single-tau channel for pair production of up-type leptoquarks $\text{LQ}_{3}^{\text{u}}$. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{u}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.

Acceptance of the middle bin of the multi-bin signal region (100 GeV $< p_{\text{T}}(\tau) <$ 200 GeV) of the single-tau channel for pair production of up-type leptoquarks $\text{LQ}_{3}^{\text{u}}$.

Efficiency of the middle bin of the multi-bin signal region (100 GeV $< p_{\text{T}}(\tau) <$ 200 GeV) of the single-tau channel for pair production of up-type leptoquarks $\text{LQ}_{3}^{\text{u}}$. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{u}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.

Acceptance of the last bin of the multi-bin signal region (200 GeV $< p_{\text{T}}(\tau)$) of the single-tau channel for pair production of up-type leptoquarks $\text{LQ}_{3}^{\text{u}}$.

Efficiency of the last bin of the multi-bin signal region (200 GeV $< p_{\text{T}}(\tau)$) of the single-tau channel for pair production of up-type leptoquarks $\text{LQ}_{3}^{\text{u}}$. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{u}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.

Acceptance of the signal region of the di-tau channel for pair production of up-type leptoquarks $\text{LQ}_{3}^{\text{u}}$.

Efficiency of the signal region of the di-tau channel for pair production of up-type leptoquarks $\text{LQ}_{3}^{\text{u}}$. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{u}} \rightarrow b\tau)$ of 0 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.

Acceptance of the one-bin signal region of the single-tau channel for pair production of down-type leptoquarks $\text{LQ}_{3}^{\text{d}}$.

Efficiency of the one-bin signal region of the single-tau channel for pair production of down-type leptoquarks $\text{LQ}_{3}^{\text{d}}$. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{d}} \rightarrow t\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.

Acceptance of the first bin of the multi-bin signal region (50 GeV $< p_{\text{T}}(\tau) <$ 100 GeV) of the single-tau channel for pair production of down-type leptoquarks $\text{LQ}_{3}^{\text{d}}$.

Efficiency of the first bin of the multi-bin signal region (50 GeV $< p_{\text{T}}(\tau) <$ 100 GeV) of the single-tau channel for pair production of down-type leptoquarks $\text{LQ}_{3}^{\text{d}}$. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{d}} \rightarrow t\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.

Acceptance of the middle bin of the multi-bin signal region (100 GeV $< p_{\text{T}}(\tau) <$ 200 GeV) of the single-tau channel for pair production of down-type leptoquarks $\text{LQ}_{3}^{\text{d}}$.

Efficiency of the middle bin of the multi-bin signal region (100 GeV $< p_{\text{T}}(\tau) <$ 200 GeV) of the single-tau channel for pair production of down-type leptoquarks $\text{LQ}_{3}^{\text{d}}$. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{d}} \rightarrow t\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.

Acceptance of the last bin of the multi-bin signal region (200 GeV $< p_{\text{T}}(\tau)$) of the single-tau channel for pair production of down-type leptoquarks $\text{LQ}_{3}^{\text{d}}$.

Efficiency of the last bin of the multi-bin signal region (200 GeV $< p_{\text{T}}(\tau)$) of the single-tau channel for pair production of down-type leptoquarks $\text{LQ}_{3}^{\text{d}}$. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{d}} \rightarrow t\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.

Acceptance of the signal region of the di-tau channel for pair production of down-type leptoquarks $\text{LQ}_{3}^{\text{d}}$.

Efficiency of the signal region of the di-tau channel for pair production of down-type leptoquarks $\text{LQ}_{3}^{\text{d}}$. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{d}} \rightarrow t\tau)$ of 0 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.

Acceptance of the one-bin signal region of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ in the minimal-coupling scenario.

Efficiency of the one-bin signal region of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ in the minimal-coupling scenario. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.

Acceptance of the first bin of the multi-bin signal region (50 GeV $< p_{\text{T}}(\tau) <$ 100 GeV) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ in the minimal-coupling scenario.

Efficiency of the first bin of the multi-bin signal region (50 GeV $< p_{\text{T}}(\tau) <$ 100 GeV) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ in the minimal-coupling scenario. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.

Acceptance of the middle bin of the multi-bin signal region (100 GeV $< p_{\text{T}}(\tau) <$ 200 GeV) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ in the minimal-coupling scenario.

Efficiency of the middle bin of the multi-bin signal region (100 GeV $< p_{\text{T}}(\tau) <$ 200 GeV) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ in the minimal-coupling scenario. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.

Acceptance of the last bin of the multi-bin signal region (200 GeV $< p_{\text{T}}(\tau)$) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ in the minimal-coupling scenario.

Efficiency of the last bin of the multi-bin signal region (200 GeV $< p_{\text{T}}(\tau)$) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ in the minimal-coupling scenario. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.

Acceptance of the signal region of the di-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ in the minimal-coupling scenario.

Efficiency of the signal region of the di-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ in the minimal-coupling scenario. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ of 0 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.

Acceptance of the one-bin signal region of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ with additional gauge couplings.

Efficiency of the one-bin signal region of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ with additional gauge couplings. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.

Acceptance of the first bin of the multi-bin signal region (50 GeV $< p_{\text{T}}(\tau) <$ 100 GeV) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ with additional gauge couplings.

Efficiency of the first bin of the multi-bin signal region (50 GeV $< p_{\text{T}}(\tau) <$ 100 GeV) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ with additional gauge couplings. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.

Acceptance of the middle bin of the multi-bin signal region (100 GeV $< p_{\text{T}}(\tau) <$ 200 GeV) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ with additional gauge couplings.

Efficiency of the middle bin of the multi-bin signal region (100 GeV $< p_{\text{T}}(\tau) <$ 200 GeV) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ with additional gauge couplings. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.

Acceptance of the last bin of the multi-bin signal region (200 GeV $< p_{\text{T}}(\tau)$) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ with additional gauge couplings.

Efficiency of the last bin of the multi-bin signal region (200 GeV $< p_{\text{T}}(\tau)$) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ with additional gauge couplings. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.

Acceptance of the signal region of the di-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ with additional gauge couplings.

Efficiency of the signal region of the di-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ with additional gauge couplings. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ of 0 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.

Acceptance of the one-bin signal region of the single-tau channel for pair production of top squarks with decays via tau sleptons.

Efficiency of the one-bin signal region of the single-tau channel for pair production of top squarks with decays via tau sleptons.

Acceptance of the first bin of the multi-bin signal region (50 GeV $< p_{\text{T}}(\tau) <$ 100 GeV) of the single-tau channel for pair production of top squarks with decays via tau sleptons.

Efficiency of the first bin of the multi-bin signal region (50 GeV $< p_{\text{T}}(\tau) <$ 100 GeV) of the single-tau channel for pair production of top squarks with decays via tau sleptons.

Acceptance of the middle bin of the multi-bin signal region (100 GeV $< p_{\text{T}}(\tau) <$ 200 GeV) of the single-tau channel for pair production of top squarks with decays via tau sleptons.

Efficiency of the middle bin of the multi-bin signal region (100 GeV $< p_{\text{T}}(\tau) <$ 200 GeV) of the single-tau channel for pair production of top squarks with decays via tau sleptons.

Acceptance of the last bin of the multi-bin signal region (200 GeV $< p_{\text{T}}(\tau)$) of the single-tau channel for pair production of top squarks with decays via tau sleptons.

Efficiency of the last bin of the multi-bin signal region (200 GeV $< p_{\text{T}}(\tau)$) of the single-tau channel for pair production of top squarks with decays via tau sleptons.

Acceptance of the signal region of the di-tau channel for pair production of top squarks with decays via tau sleptons.

Efficiency of the signal region of the di-tau channel for pair production of top squarks with decays via tau sleptons.

Cutflow for the benchmark signal model $m(\tilde{t}_{1}) = 1350$ GeV, $m(\tilde{\tau}_{1}) = 1090$ GeV for the di-tau SR. The simulated sample contains 30,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the di-tau channel.

Cutflow for the benchmark signal model $m(\tilde{t}_{1}) = 1350$ GeV, $m(\tilde{\tau}_{1}) = 1090$ GeV for the single-tau one-bin SR. The simulated sample contains 30,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the single-tau channel.

Cutflow for the benchmark signal model $m(\tilde{t}_{1}) = 1350$ GeV, $m(\tilde{\tau}_{1}) = 1090$ GeV for the single-tau multi-bin SR. The simulated sample contains 30,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the single-tau channel.

Cutflow for the benchmark signal model $m(\text{LQ}_{3}^{\text{u}}) = 1.2$ TeV, $\beta = 0.5$ for the di-tau SR. The simulated sample contains 210,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the di-tau channel.

Cutflow for the benchmark signal model $m(\text{LQ}_{3}^{\text{u}}) = 1.2$ TeV, $\beta = 0.5$ for the single-tau one-bin SR. The simulated sample contains 210,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the single-tau channel.

Cutflow for the benchmark signal model $m(\text{LQ}_{3}^{\text{u}}) = 1.2$ TeV, $\beta = 0.5$ for the single-tau multi-bin SR. The simulated sample contains 210,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the single-tau channel.

Cutflow for the benchmark signal model $m(\text{LQ}_{3}^{\text{d}}) = 1.2$ TeV, $\beta = 0.5$ for the di-tau SR. The simulated sample contains 210,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the di-tau channel.

Cutflow for the benchmark signal model $m(\text{LQ}_{3}^{\text{d}}) = 1.2$ TeV, $\beta = 0.5$ for the single-tau one-bin SR. The simulated sample contains 210,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the single-tau channel.

Cutflow for the benchmark signal model $m(\text{LQ}_{3}^{\text{d}}) = 1.2$ TeV, $\beta = 0.5$ for the single-tau multi-bin SR. The simulated sample contains 210,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the single-tau channel.

Cutflow for the benchmark signal model $m(\text{LQ}_{3}^{\text{v}}) = 1.4$ TeV, $\beta = 0.5$ in the minimal-coupling scenario for the di-tau SR. The simulated sample contains 50,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the di-tau channel.

Cutflow for the benchmark signal model $m(\text{LQ}_{3}^{\text{v}}) = 1.4$ TeV, $\beta = 0.5$ in the minimal-coupling scenario for the single-tau one-bin SR. The simulated sample contains 50,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the single-tau channel.

Cutflow for the benchmark signal model $m(\text{LQ}_{3}^{\text{v}}) = 1.4$ TeV, $\beta = 0.5$ in the minimal-coupling scenario for the single-tau multi-bin SR. The simulated sample contains 50,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the single-tau channel.

Cutflow for the benchmark signal model $m(\text{LQ}_{3}^{\text{v}}) = 1.4$ TeV, $\beta = 0.5$ in the Yang--Mills scenario for the di-tau SR. The simulated sample contains 50,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the di-tau channel.

Cutflow for the benchmark signal model $m(\text{LQ}_{3}^{\text{v}}) = 1.4$ TeV, $\beta = 0.5$ in the Yang--Mills scenario for the single-tau one-bin SR. The simulated sample contains 50,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the single-tau channel.

Cutflow for the benchmark signal model $m(\text{LQ}_{3}^{\text{v}}) = 1.4$ TeV, $\beta = 0.5$ in the Yang--Mills scenario for the single-tau multi-bin SR. The simulated sample contains 50,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the single-tau channel.

The rejection factor (inverse of the efficiency) for jets that have the other origins (background jets) are shown. The background jet rejection factor is calculated using pre-selected large-$R$ jets in the sample of simulated $Z\rightarrow\nu\nu$ + jets events, dominated by initial state radiation (ISR) jets. The efficiency correction factors are applied on the background rejection for the $W_{qq}$/$Z_{qq}$-tagging. The systematic uncertainty is represented by the hashed bands.

The boson-tagging efficiency for jets arising from $Z/h$ bosons decaying into $b\bar{b}$ (signal jets). The signal jet efficiency of $Z_{bb}$/$h_{bb}$-tagging is evaluated using a sample of pre-selected large-$R$ jets ($p_{\textrm{T}}>200~\textrm{GeV}, |\eta|<2.0, m_{J} > 40~\textrm{GeV}$) in the simulated $(\tilde{W},\tilde{B})$ simplified model signal events with $\Delta m(\tilde{\chi}_{\textrm{heavy}},~\tilde{\chi}_{\textrm{light}}) \ge 400~\textrm{GeV}$. The jets are matched with generator-level $Z/h$-bosons by $\Delta R<1.0$ which decay into $b\bar{b}$. The systematic uncertainty is represented by the hashed bands.

The rejection factor (inverse of the efficiency) for jets that have the other origins (background jets) are shown. The background jet rejection factor is calculated using pre-selected large-$R$ jets in the sample of simulated $Z\rightarrow\nu\nu$ + jets events, dominated by initial state radiation (ISR) jets. As for the $Z_{bb}$/$h_{bb}$-tagging, the rejection is shown as the function of number of $b$- or $c$-quarks contained in the large-$R$ jet within $\Delta R<1.0$. The systematic uncertainty is represented by the hashed bands.

The signal jet efficiency and background jet rejection for the $W_{qq}$-/$Z_{qq}$-tagging working point used in the analysis in comparison with those for the nominal working points (''50% efficiency W/Z tagger'' in ATL-PHYS-PUB-2020-017). The definition of the efficiency and rejection follow the caption of Figure 4. Note that the efficiency for the nominal working point is not 50% since they are tuned using jet samples with different pre-selection.

The signal jet efficiency and background jet rejection for the $W_{qq}$-/$Z_{qq}$-tagging working point used in the analysis in comparison with those for the nominal working points (''50% efficiency W/Z tagger'' in ATL-PHYS-PUB-2020-017). The definition of the efficiency and rejection follow the caption of Figure 4. Note that the efficiency for the nominal working point is not 50% since they are tuned using jet samples with different pre-selection.

The signal jet efficiency and background jet rejection for the $W_{qq}$-/$Z_{qq}$-tagging working point used in the analysis in comparison with those for the nominal working points (''50% efficiency W/Z tagger'' in ATL-PHYS-PUB-2020-017). The definition of the efficiency and rejection follow the caption of Figure 4. Note that the efficiency for the nominal working point is not 50% since they are tuned using jet samples with different pre-selection.

The signal jet efficiency and background jet rejection for the $W_{qq}$-/$Z_{qq}$-tagging working point used in the analysis in comparison with those for the nominal working points (''50% efficiency W/Z tagger'' in ATL-PHYS-PUB-2020-017). The definition of the efficiency and rejection follow the caption of Figure 4. Note that the efficiency for the nominal working point is not 50% since they are tuned using jet samples with different pre-selection.

The total post-fit uncertainty in each of the SRs and VRs.

Summary of the observed data and predicted SM background in all SRs. The background prediction in SR-4Q (SR-2B2Q) is obtained by a background-only fit to CR0L-4Q (CR0L-2B2Q). The total systematic uncertainty on the background prediction is shown by the hatched area. Distributions of a few representative signals are overlaid. A few representative signals are overlaid. For the $(\tilde{W},\tilde{B})$ simplified model models, the label $(x,y)$ indicates $(m(\tilde{\chi}_{1}^{\pm}), m(\tilde{\chi}_{1}^{0}))=(x,y)~\textrm{GeV}$. The bottom panel shows the statistical significance of the discrepancy between the observed number of events and the SM expectation.

Number of observed data events and the SM backgrounds in the SRs and the CR0L bins. The SM backgrounds are predicted by the background-only fits. Note that the relative uncertainty on the expected yield in the CRs between the reducible backgrounds are identical, given that a common normalization factor is assigned for all of them in the fit. Yields for negligible backgrounds are indicated by "0.0000001±0.0000001" in the table.

Number of observed data events and the post-fit SM background prediction in the VR1L(1Y) bins and the corresponding CR1L(1Y) bins. "-" indicates negligibly small contribution. Note that the relative uncertainty on the expected yield in the CRs between the reducible backgrounds are identical, given that a common normalization factor is assigned for all of them in the fit. Yields for negligible backgrounds are indicated by "0.0000001±0.0000001" in the table.

$m_{\textrm{eff}}$ distribution in SR-4Q-VV. The post-fit SM background expectation using the background-only fit is shown in a histogram stack. Distributions of a few representative signals are overlaid. The bottom panels show the ratio of the observed data to the background prediction. The selection criteria on the variable shown by each plot is removed, while the arrow indicates the cut value to define the region. A few representative signals are overlaid. For the $(\tilde{W},\tilde{B})$ simplified model models, the label $(x,y)$ indicates $(m(\tilde{\chi}_{1}^{\pm}), m(\tilde{\chi}_{1}^{0}))=(x,y)~\text{GeV}$.

Distribution of $m(J_{1})$ in SR-4Q-VV. The post-fit SM background expectation using the background-only fit is shown in a histogram stack. Distributions of relevant signals are overlaid. The bottom panels show the ratio of the observed data to the background prediction. The selection criteria on the variable shown by each plot is removed, while the arrow indicates the cut value to define the region. A few representative signals are overlaid. For the $(\tilde{W},\tilde{B})$ simplified model models, the label $(x,y)$ indicates $(m(\tilde{\chi}_{1}^{\pm}), m(\tilde{\chi}_{1}^{0}))=(x,y)~\text{GeV}$.

Distribution of $D_2(J_{1})$ in SR-4Q-VV. For $D_2$, the cut value applied for $V_{qq}$-tagging ($D_{2,\text{cut}}$) is subtracted as the off-set so that $D_2-D_{2,\text{cut}}(J)<0$ represents $J$ passing the $D_2$ selection. The post-fit SM background expectation using the background-only fit is shown in a histogram stack. Distributions of relevant signals are overlaid. The bottom panels show the ratio of the observed data to the background prediction. The selection criteria on the variable shown by each plot is removed, while the arrow indicates the cut value to define the region. A few representative signals are overlaid. For the $(\tilde{W},\tilde{B})$ simplified model models, the label $(x,y)$ indicates $(m(\tilde{\chi}_{1}^{\pm}), m(\tilde{\chi}_{1}^{0}))=(x,y)~\text{GeV}$.

Distribution of $m(J_{2})$ in SR-4Q-VV. The post-fit SM background expectation using the background-only fit is shown in a histogram stack. Distributions of relevant signals are overlaid. The bottom panels show the ratio of the observed data to the background prediction. The selection criteria on the variable shown by each plot is removed, while the arrow indicates the cut value to define the region. A few representative signals are overlaid. For the $(\tilde{W},\tilde{B})$ simplified model models, the label $(x,y)$ indicates $(m(\tilde{\chi}_{1}^{\pm}), m(\tilde{\chi}_{1}^{0}))=(x,y)~\text{GeV}$.

Distribution of $D_2(J_{2})$ in SR-4Q-VV. For $D_2$, the cut value applied for $V_{qq}$-tagging ($D_{2,\text{cut}}$) is subtracted as the off-set so that $D_2-D_{2,\text{cut}}(J)<0$ represents $J$ passing the $D_2$ selection. The post-fit SM background expectation using the background-only fit is shown in a histogram stack. Distributions of relevant signals are overlaid. The bottom panels show the ratio of the observed data to the background prediction. The selection criteria on the variable shown by each plot is removed, while the arrow indicates the cut value to define the region. A few representative signals are overlaid. For the $(\tilde{W},\tilde{B})$ simplified model models, the label $(x,y)$ indicates $(m(\tilde{\chi}_{1}^{\pm}), m(\tilde{\chi}_{1}^{0}))=(x,y)~\text{GeV}$.

$m_{\textrm{T2}}$ distributions in SR-2B2Q-VZ. The post-fit SM background expectation using the background-only fit is shown in a histogram stack. Distributions of a few representative signals are overlaid. The bottom panels show the ratio of the observed data to the background prediction. The selection criteria on the variable shown by each plot is removed, while the arrow indicates the cut value to define the region. A few representative signals are overlaid. For the $(\tilde{W},\tilde{B})$ simplified model models, the label $(x,y)$ indicates $(m(\tilde{\chi}_{1}^{\pm}), m(\tilde{\chi}_{1}^{0}))=(x,y)~\text{GeV}$.

Distribution of $m(J_{bb})$ in SR-2B2Q-VZ. The post-fit SM background expectation using the background-only fit is shown in a histogram stack. Distributions of relevant signals are overlaid. The bottom panels show the ratio of the observed data to the background prediction. The selection criteria on the variable shown by each plot is removed, while the arrow indicates the cut value to define the region. A few representative signals are overlaid. For the $(\tilde{W},\tilde{B})$ simplified model models, the label $(x,y)$ indicates $(m(\tilde{\chi}_{1}^{\pm}), m(\tilde{\chi}_{1}^{0}))=(x,y)~\text{GeV}$.

Distribution of $m_{\textrm{eff}} $ in SR-2B2Q-VZ. The post-fit SM background expectation using the background-only fit is shown in a histogram stack. Distributions of relevant signals are overlaid. The bottom panels show the ratio of the observed data to the background prediction. The selection criteria on the variable shown by each plot is removed, while the arrow indicates the cut value to define the region. A few representative signals are overlaid. For the $(\tilde{W},\tilde{B})$ simplified model models, the label $(x,y)$ indicates $(m(\tilde{\chi}_{1}^{\pm}), m(\tilde{\chi}_{1}^{0}))=(x,y)~\text{GeV}$.

$m_{\textrm{T2}}$ distributions in SR-2B2Q-Vh. The post-fit SM background expectation using the background-only fit is shown in a histogram stack. Distributions of a few representative signals are overlaid. The bottom panels show the ratio of the observed data to the background prediction. The selection criteria on the variable shown by each plot is removed, while the arrow indicates the cut value to define the region. A few representative signals are overlaid. For the $(\tilde{W},\tilde{B})$ simplified model models, the label $(x,y)$ indicates $(m(\tilde{\chi}_{1}^{\pm}), m(\tilde{\chi}_{1}^{0}))=(x,y)~\text{GeV}$.

Distribution of $m(J_{bb})$ in SR-2B2Q-Vh. The post-fit SM background expectation using the background-only fit is shown in a histogram stack. Distributions of relevant signals are overlaid. The bottom panels show the ratio of the observed data to the background prediction. The selection criteria on the variable shown by each plot is removed, while the arrow indicates the cut value to define the region. A few representative signals are overlaid. For the $(\tilde{W},\tilde{B})$ simplified model models, the label $(x,y)$ indicates $(m(\tilde{\chi}_{1}^{\pm}), m(\tilde{\chi}_{1}^{0}))=(x,y)~\text{GeV}$.

Distribution of $m_{\textrm{eff}} $ in SR-2B2Q-Vh. The post-fit SM background expectation using the background-only fit is shown in a histogram stack. Distributions of relevant signals are overlaid. The bottom panels show the ratio of the observed data to the background prediction. The selection criteria on the variable shown by each plot is removed, while the arrow indicates the cut value to define the region. A few representative signals are overlaid. For the $(\tilde{W},\tilde{B})$ simplified model models, the label $(x,y)$ indicates $(m(\tilde{\chi}_{1}^{\pm}), m(\tilde{\chi}_{1}^{0}))=(x,y)~\text{GeV}$.

Exclusion limits for $(\tilde{W},\tilde{B})$ simplifiec model as a function of the produced wino mass ($m(\tilde{\chi}_{1}^{\pm}/\tilde{\chi}_{2}^{0})$) and the bino LSP mass ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed) and observed (solid) 95% CL exclusion limits on $(\tilde{W},\tilde{B})$ simplified models; C1C1-WW. The expected limit for the 1$\sigma$ down variation is not shown as no mass points could be excluded.

Exclusion limits for $(\tilde{W},\tilde{B})$ simplifiec model as a function of the produced wino mass ($m(\tilde{\chi}_{1}^{\pm}/\tilde{\chi}_{2}^{0})$) and the bino LSP mass ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed) and observed (solid) 95% CL exclusion limits on $(\tilde{W},\tilde{B})$ simplified models; C1C1-WW. The expected limit for the 1$\sigma$ down variation is not shown as no mass points could be excluded.

Exclusion limits for $(\tilde{W},\tilde{B})$ simplifiec model as a function of the produced wino mass ($m(\tilde{\chi}_{1}^{\pm}/\tilde{\chi}_{2}^{0})$) and the bino LSP mass ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed) and observed (solid) 95% CL exclusion limits on $(\tilde{W},\tilde{B})$ simplified models; C1C1-WW. The expected limit for the 1$\sigma$ down variation is not shown as no mass points could be excluded.

Exclusion limits for $(\tilde{W},\tilde{B})$ simplifiec model as a function of the produced wino mass ($m(\tilde{\chi}_{1}^{\pm}/\tilde{\chi}_{2}^{0})$) and the bino LSP mass ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed) and observed (solid) 95% CL exclusion limits on $(\tilde{W},\tilde{B})$ simplified models; C1C1-WW. The expected limit for the 1$\sigma$ down variation is not shown as no mass points could be excluded.

Exclusion limits for $(\tilde{W},\tilde{B})$ simplifiec model as a function of the produced wino mass ($m(\tilde{\chi}_{1}^{\pm}/\tilde{\chi}_{2}^{0})$) and the bino LSP mass ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed) and observed (solid) 95% CL exclusion limits on $(\tilde{W},\tilde{B})$ simplified models; C1C1-WW. The expected limit for the 1$\sigma$ down variation is not shown as no mass points could be excluded.

Exclusion limits for $(\tilde{W},\tilde{B})$ simplifiec model as a function of the produced wino mass ($m(\tilde{\chi}_{1}^{\pm}/\tilde{\chi}_{2}^{0})$) and the bino LSP mass ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed) and observed (solid) 95% CL exclusion limits on $(\tilde{W},\tilde{B})$ simplified models; C1N2-WZ.

Exclusion limits for $(\tilde{W},\tilde{B})$ simplifiec model as a function of the produced wino mass ($m(\tilde{\chi}_{1}^{\pm}/\tilde{\chi}_{2}^{0})$) and the bino LSP mass ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed) and observed (solid) 95% CL exclusion limits on $(\tilde{W},\tilde{B})$ simplified models; C1N2-WZ.

Exclusion limits for $(\tilde{W},\tilde{B})$ simplifiec model as a function of the produced wino mass ($m(\tilde{\chi}_{1}^{\pm}/\tilde{\chi}_{2}^{0})$) and the bino LSP mass ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed) and observed (solid) 95% CL exclusion limits on $(\tilde{W},\tilde{B})$ simplified models; C1N2-WZ.

Exclusion limits for $(\tilde{W},\tilde{B})$ simplifiec model as a function of the produced wino mass ($m(\tilde{\chi}_{1}^{\pm}/\tilde{\chi}_{2}^{0})$) and the bino LSP mass ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed) and observed (solid) 95% CL exclusion limits on $(\tilde{W},\tilde{B})$ simplified models; C1N2-WZ.

Exclusion limits for $(\tilde{W},\tilde{B})$ simplifiec model as a function of the produced wino mass ($m(\tilde{\chi}_{1}^{\pm}/\tilde{\chi}_{2}^{0})$) and the bino LSP mass ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed) and observed (solid) 95% CL exclusion limits on $(\tilde{W},\tilde{B})$ simplified models; C1N2-WZ.

Exclusion limits for $(\tilde{W},\tilde{B})$ simplifiec model as a function of the produced wino mass ($m(\tilde{\chi}_{1}^{\pm}/\tilde{\chi}_{2}^{0})$) and the bino LSP mass ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed) and observed (solid) 95% CL exclusion limits on $(\tilde{W},\tilde{B})$ simplified models; C1N2-WZ.

Exclusion limits for $(\tilde{W},\tilde{B})$ simplifiec model as a function of the produced wino mass ($m(\tilde{\chi}_{1}^{\pm}/\tilde{\chi}_{2}^{0})$) and the bino LSP mass ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed) and observed (solid) 95% CL exclusion limits on $(\tilde{W},\tilde{B})$ simplified models; C1N2-Wh.

Exclusion limits for $(\tilde{W},\tilde{B})$ simplifiec model as a function of the produced wino mass ($m(\tilde{\chi}_{1}^{\pm}/\tilde{\chi}_{2}^{0})$) and the bino LSP mass ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed) and observed (solid) 95% CL exclusion limits on $(\tilde{W},\tilde{B})$ simplified models; C1N2-Wh.

Exclusion limits for $(\tilde{W},\tilde{B})$ simplifiec model as a function of the produced wino mass ($m(\tilde{\chi}_{1}^{\pm}/\tilde{\chi}_{2}^{0})$) and the bino LSP mass ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed) and observed (solid) 95% CL exclusion limits on $(\tilde{W},\tilde{B})$ simplified models; C1N2-Wh.

Exclusion limits for $(\tilde{W},\tilde{B})$ simplifiec model as a function of the produced wino mass ($m(\tilde{\chi}_{1}^{\pm}/\tilde{\chi}_{2}^{0})$) and the bino LSP mass ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed) and observed (solid) 95% CL exclusion limits on $(\tilde{W},\tilde{B})$ simplified models; C1N2-Wh.

Exclusion limits for $(\tilde{W},\tilde{B})$ simplifiec model as a function of the produced wino mass ($m(\tilde{\chi}_{1}^{\pm}/\tilde{\chi}_{2}^{0})$) and the bino LSP mass ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed) and observed (solid) 95% CL exclusion limits on $(\tilde{W},\tilde{B})$ simplified models; C1N2-Wh.

Exclusion limits for $(\tilde{W},\tilde{B})$ simplifiec model as a function of the produced wino mass ($m(\tilde{\chi}_{1}^{\pm}/\tilde{\chi}_{2}^{0})$) and the bino LSP mass ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed) and observed (solid) 95% CL exclusion limits on $(\tilde{W},\tilde{B})$ simplified models; C1N2-Wh.

Exclusion limits for the $(\tilde{W},\tilde{B})$ and $(\tilde{H},\tilde{B})$ models shown as a function of the mass of wino/higgsino chargino ($m(\tilde{\chi}_{1}^{\pm})$) and the mass of bino LSP ($m(\tilde{\chi}_{1}^{0})$). Expected limits for various $\mathcal{B}(\tilde{\chi}_{2}^{0} \rightarrow Z \tilde{\chi}_{1}^{0})$ hypotheses overlaid. The outer and inner bundles correspond to the limits for the $(\tilde{W},\tilde{B})$ and $(\tilde{H},\tilde{B})$ models respectively.

Exclusion limits for the $(\tilde{W},\tilde{B})$ and $(\tilde{H},\tilde{B})$ models shown as a function of the mass of wino/higgsino chargino ($m(\tilde{\chi}_{1}^{\pm})$) and the mass of bino LSP ($m(\tilde{\chi}_{1}^{0})$). Observed limits for various $\mathcal{B}(\tilde{\chi}_{2}^{0} \rightarrow Z \tilde{\chi}_{1}^{0})$ hypotheses overlaid. The outer and inner bundles correspond to the limits for the $(\tilde{W},\tilde{B})$ and $(\tilde{H},\tilde{B})$ models respectively.

Exclusion limits for the $(\tilde{W},\tilde{B})$ and $(\tilde{H},\tilde{B})$ models shown as a function of the mass of wino/higgsino chargino ($m(\tilde{\chi}_{1}^{\pm})$) and the mass of bino LSP ($m(\tilde{\chi}_{1}^{0})$). Expected limits for various $\mathcal{B}(\tilde{\chi}_{2}^{0} \rightarrow Z \tilde{\chi}_{1}^{0})$ hypotheses overlaid. The outer and inner bundles correspond to the limits for the $(\tilde{W},\tilde{B})$ and $(\tilde{H},\tilde{B})$ models respectively.

Exclusion limits for the $(\tilde{W},\tilde{B})$ and $(\tilde{H},\tilde{B})$ models shown as a function of the mass of wino/higgsino chargino ($m(\tilde{\chi}_{1}^{\pm})$) and the mass of bino LSP ($m(\tilde{\chi}_{1}^{0})$). Observed limits for various $\mathcal{B}(\tilde{\chi}_{2}^{0} \rightarrow Z \tilde{\chi}_{1}^{0})$ hypotheses overlaid. The outer and inner bundles correspond to the limits for the $(\tilde{W},\tilde{B})$ and $(\tilde{H},\tilde{B})$ models respectively.

Exclusion limits for the $(\tilde{W},\tilde{B})$ and $(\tilde{H},\tilde{B})$ models shown as a function of the mass of wino/higgsino chargino ($m(\tilde{\chi}_{1}^{\pm})$) and the mass of bino LSP ($m(\tilde{\chi}_{1}^{0})$). Expected limits for various $\mathcal{B}(\tilde{\chi}_{2}^{0} \rightarrow Z \tilde{\chi}_{1}^{0})$ hypotheses overlaid. The outer and inner bundles correspond to the limits for the $(\tilde{W},\tilde{B})$ and $(\tilde{H},\tilde{B})$ models respectively.

Exclusion limits for the $(\tilde{W},\tilde{B})$ models shown as a function of the mass of wino/higgsino chargino ($m(\tilde{\chi}_{1}^{\pm})$) and the mass of bino LSP ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed) and observed (solid red) 95% CL exclusion limits for a representative branching ratio $\mathcal{B}(\tilde{\chi}_{2}^{0} \rightarrow Z\tilde{\chi}_{1}^{0})=50$%.

Exclusion limits for the $(\tilde{W},\tilde{B})$ models shown as a function of the mass of wino/higgsino chargino ($m(\tilde{\chi}_{1}^{\pm})$) and the mass of bino LSP ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed) and observed (solid red) 95% CL exclusion limits for a representative branching ratio $\mathcal{B}(\tilde{\chi}_{2}^{0} \rightarrow Z\tilde{\chi}_{1}^{0})=50$%.

Exclusion limits for the $(\tilde{W},\tilde{B})$ and $(\tilde{H},\tilde{B})$ models shown as a function of the mass of wino/higgsino chargino ($m(\tilde{\chi}_{1}^{\pm})$) and the mass of bino LSP ($m(\tilde{\chi}_{1}^{0})$). Observed limits for various $\mathcal{B}(\tilde{\chi}_{2}^{0} \rightarrow Z \tilde{\chi}_{1}^{0})$ hypotheses overlaid. The outer and inner bundles correspond to the limits for the $(\tilde{W},\tilde{B})$ and $(\tilde{H},\tilde{B})$ models respectively.

Exclusion limits for the $(\tilde{W},\tilde{B})$ models shown as a function of the mass of wino/higgsino chargino ($m(\tilde{\chi}_{1}^{\pm})$) and the mass of bino LSP ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed) and observed (solid red) 95% CL exclusion limits for a representative branching ratio $\mathcal{B}(\tilde{\chi}_{2}^{0} \rightarrow Z\tilde{\chi}_{1}^{0})=50$%.

Exclusion limits for the $(\tilde{W},\tilde{B})$ models shown as a function of the mass of wino/higgsino chargino ($m(\tilde{\chi}_{1}^{\pm})$) and the mass of bino LSP ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed) and observed (solid red) 95% CL exclusion limits for a representative branching ratio $\mathcal{B}(\tilde{\chi}_{2}^{0} \rightarrow Z\tilde{\chi}_{1}^{0})=50$%.

Exclusion limits for the $(\tilde{W},\tilde{B})$ and $(\tilde{H},\tilde{B})$ models shown as a function of the mass of wino/higgsino chargino ($m(\tilde{\chi}_{1}^{\pm})$) and the mass of bino LSP ($m(\tilde{\chi}_{1}^{0})$). Expected limits for various $\mathcal{B}(\tilde{\chi}_{2}^{0} \rightarrow Z \tilde{\chi}_{1}^{0})$ hypotheses overlaid. The outer and inner bundles correspond to the limits for the $(\tilde{W},\tilde{B})$ and $(\tilde{H},\tilde{B})$ models respectively.

Exclusion limits for the $(\tilde{W},\tilde{B})$ and $(\tilde{H},\tilde{B})$ models shown as a function of the mass of wino/higgsino chargino ($m(\tilde{\chi}_{1}^{\pm})$) and the mass of bino LSP ($m(\tilde{\chi}_{1}^{0})$). Observed limits for various $\mathcal{B}(\tilde{\chi}_{2}^{0} \rightarrow Z \tilde{\chi}_{1}^{0})$ hypotheses overlaid. The outer and inner bundles correspond to the limits for the $(\tilde{W},\tilde{B})$ and $(\tilde{H},\tilde{B})$ models respectively.

Exclusion limits for the $(\tilde{W},\tilde{B})$ and $(\tilde{H},\tilde{B})$ models shown as a function of the mass of wino/higgsino chargino ($m(\tilde{\chi}_{1}^{\pm})$) and the mass of bino LSP ($m(\tilde{\chi}_{1}^{0})$). Expected limits for various $\mathcal{B}(\tilde{\chi}_{2}^{0} \rightarrow Z \tilde{\chi}_{1}^{0})$ hypotheses overlaid. The outer and inner bundles correspond to the limits for the $(\tilde{W},\tilde{B})$ and $(\tilde{H},\tilde{B})$ models respectively.

Exclusion limits for the $(\tilde{W},\tilde{B})$ and $(\tilde{H},\tilde{B})$ models shown as a function of the mass of wino/higgsino chargino ($m(\tilde{\chi}_{1}^{\pm})$) and the mass of bino LSP ($m(\tilde{\chi}_{1}^{0})$). Observed limits for various $\mathcal{B}(\tilde{\chi}_{2}^{0} \rightarrow Z \tilde{\chi}_{1}^{0})$ hypotheses overlaid. The outer and inner bundles correspond to the limits for the $(\tilde{W},\tilde{B})$ and $(\tilde{H},\tilde{B})$ models respectively.

Exclusion limits for the $(\tilde{W},\tilde{B})$ and $(\tilde{H},\tilde{B})$ models shown as a function of the mass of wino/higgsino chargino ($m(\tilde{\chi}_{1}^{\pm})$) and the mass of bino LSP ($m(\tilde{\chi}_{1}^{0})$). Expected limits for various $\mathcal{B}(\tilde{\chi}_{2}^{0} \rightarrow Z \tilde{\chi}_{1}^{0})$ hypotheses overlaid. The outer and inner bundles correspond to the limits for the $(\tilde{W},\tilde{B})$ and $(\tilde{H},\tilde{B})$ models respectively. The expected limit for the 1$\sigma$ down variation is not shown as no mass points could be excluded.

Exclusion limits for the $(\tilde{H},\tilde{B})$ models shown as a function of the mass of wino/higgsino chargino ($m(\tilde{\chi}_{1}^{\pm})$) and the mass of bino LSP ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed) and observed (solid red) 95% CL exclusion limits for a representative branching ratio $\mathcal{B}(\tilde{\chi}_{2}^{0} \rightarrow Z\tilde{\chi}_{1}^{0})=50$%. The expected limit for the 1$\sigma$ down variation is not shown as no mass points could be excluded.

Exclusion limits for the $(\tilde{W},\tilde{B})$ and $(\tilde{H},\tilde{B})$ models shown as a function of the mass of wino/higgsino chargino ($m(\tilde{\chi}_{1}^{\pm})$) and the mass of bino LSP ($m(\tilde{\chi}_{1}^{0})$). Observed limits for various $\mathcal{B}(\tilde{\chi}_{2}^{0} \rightarrow Z \tilde{\chi}_{1}^{0})$ hypotheses overlaid. The outer and inner bundles correspond to the limits for the $(\tilde{W},\tilde{B})$ and $(\tilde{H},\tilde{B})$ models respectively. The expected limit for the 1$\sigma$ down variation is not shown as no mass points could be excluded.

Exclusion limits for the $(\tilde{H},\tilde{B})$ models shown as a function of the mass of wino/higgsino chargino ($m(\tilde{\chi}_{1}^{\pm})$) and the mass of bino LSP ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed) and observed (solid red) 95% CL exclusion limits for a representative branching ratio $\mathcal{B}(\tilde{\chi}_{2}^{0} \rightarrow Z\tilde{\chi}_{1}^{0})=50$%. The expected limit for the 1$\sigma$ down variation is not shown as no mass points could be excluded.

Exclusion limits for the $(\tilde{H},\tilde{B})$ models shown as a function of the mass of wino/higgsino chargino ($m(\tilde{\chi}_{1}^{\pm})$) and the mass of bino LSP ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed) and observed (solid red) 95% CL exclusion limits for a representative branching ratio $\mathcal{B}(\tilde{\chi}_{2}^{0} \rightarrow Z\tilde{\chi}_{1}^{0})=50$%. The expected limit for the 1$\sigma$ down variation is not shown as no mass points could be excluded.

95% CL exclusion limits for the $(\tilde{W},\tilde{H})$ models. The limits are projected on to a two-dimensional plane of the physical electroweakino masses $(m(\tilde{\chi}_{2}^{\pm}),m(\tilde{\chi}_{1}^{0}))$ representing $(m(\tilde{\chi}_{\textrm{heavy}}),m(\tilde{\chi}_{\textrm{light}}))$.

95% CL exclusion limits for the $(\tilde{W},\tilde{H})$ models. The limits are projected on to a two-dimensional plane of the physical electroweakino masses $(m(\tilde{\chi}_{2}^{\pm}),m(\tilde{\chi}_{1}^{0}))$ representing $(m(\tilde{\chi}_{\textrm{heavy}}),m(\tilde{\chi}_{\textrm{light}}))$.

95% CL exclusion limits for the $(\tilde{W},\tilde{H})$ models. The limits are projected on to a two-dimensional plane of the physical electroweakino masses $(m(\tilde{\chi}_{2}^{\pm}),m(\tilde{\chi}_{1}^{0}))$ representing $(m(\tilde{\chi}_{\textrm{heavy}}),m(\tilde{\chi}_{\textrm{light}}))$.

95% CL exclusion limits for the $(\tilde{W},\tilde{H})$ models. The limits are projected on to a two-dimensional plane of the physical electroweakino masses $(m(\tilde{\chi}_{2}^{\pm}),m(\tilde{\chi}_{1}^{0}))$ representing $(m(\tilde{\chi}_{\textrm{heavy}}),m(\tilde{\chi}_{\textrm{light}}))$.

95% CL exclusion limits for the $(\tilde{W},\tilde{H})$ models. The limits are projected on to a two-dimensional plane of the physical electroweakino masses $(m(\tilde{\chi}_{2}^{\pm}),m(\tilde{\chi}_{1}^{0}))$ representing $(m(\tilde{\chi}_{\textrm{heavy}}),m(\tilde{\chi}_{\textrm{light}}))$.

95% CL exclusion limits for the $(\tilde{W},\tilde{H})$ models. The limits are projected on to a two-dimensional plane of the physical electroweakino masses $(m(\tilde{\chi}_{2}^{\pm}),m(\tilde{\chi}_{1}^{0}))$ representing $(m(\tilde{\chi}_{\textrm{heavy}}),m(\tilde{\chi}_{\textrm{light}}))$.

95% CL exclusion limits for the $(\tilde{H},\tilde{W})$ models. The limits are projected on to a two-dimensional plane of the physical electroweakino masses $(m(\tilde{\chi}_{2}^{\pm}),m(\tilde{\chi}_{1}^{0}))$ representing $(m(\tilde{\chi}_{\textrm{heavy}}),m(\tilde{\chi}_{\textrm{light}}))$. The expected limit for the 1$\sigma$ down variation is not shown as no mass points could be excluded.

95% CL exclusion limits for the $(\tilde{H},\tilde{W})$ models. The limits are projected on to a two-dimensional plane of the physical electroweakino masses $(m(\tilde{\chi}_{2}^{\pm}),m(\tilde{\chi}_{1}^{0}))$ representing $(m(\tilde{\chi}_{\textrm{heavy}}),m(\tilde{\chi}_{\textrm{light}}))$. The expected limit for the 1$\sigma$ down variation is not shown as no mass points could be excluded.

95% CL exclusion limits for the $(\tilde{H},\tilde{W})$ models. The limits are projected on to a two-dimensional plane of the physical electroweakino masses $(m(\tilde{\chi}_{2}^{\pm}),m(\tilde{\chi}_{1}^{0}))$ representing $(m(\tilde{\chi}_{\textrm{heavy}}),m(\tilde{\chi}_{\textrm{light}}))$. The expected limit for the 1$\sigma$ down variation is not shown as no mass points could be excluded.

95% CL exclusion limits for the $(\tilde{H},\tilde{W})$ models. The limits are projected on to a two-dimensional plane of the physical electroweakino masses $(m(\tilde{\chi}_{2}^{\pm}),m(\tilde{\chi}_{1}^{0}))$ representing $(m(\tilde{\chi}_{\textrm{heavy}}),m(\tilde{\chi}_{\textrm{light}}))$. The expected limit for the 1$\sigma$ down variation is not shown as no mass points could be excluded.

95% CL exclusion limits for the $(\tilde{H},\tilde{W})$ models. The limits are projected on to a two-dimensional plane of the physical electroweakino masses $(m(\tilde{\chi}_{2}^{\pm}),m(\tilde{\chi}_{1}^{0}))$ representing $(m(\tilde{\chi}_{\textrm{heavy}}),m(\tilde{\chi}_{\textrm{light}}))$. The expected limit for the 1$\sigma$ down variation is not shown as no mass points could be excluded.

95% CL exclusion limits for the $(\tilde{W},\tilde{H})$ models. The limits are projected on to a two-dimensional plane as a function of the wino/higgsino mass parameters: $(M_2,\mu)$. For the limits shown on the $(M_2,\mu)$ plane, the excluded regions are indicated by the area inside the contours. The round excluded area in the top part corresponds to the excluded parameter space in the $(\tilde{W},~\tilde{H})$ model $(M_{2} > |\mu|)$, while the two small areas in at the bottom are that in the $(\tilde{H},~\tilde{W})$ model $(M_{2} < |\mu|)$.

95% CL exclusion limits for the $(\tilde{W},\tilde{H})$ models. The limits are projected on to a two-dimensional plane as a function of the wino/higgsino mass parameters: $(M_2,\mu)$. For the limits shown on the $(M_2,\mu)$ plane, the excluded regions are indicated by the area inside the contours. The expected limits for the 1$\sigma$ down variation are not shown as no mass points could be excluded. The round excluded area in the top part corresponds to the excluded parameter space in the $(\tilde{W},~\tilde{H})$ model $(M_{2} > |\mu|)$, while the two small areas in at the bottom are that in the $(\tilde{H},~\tilde{W})$ model $(M_{2} < |\mu|)$.

95% CL exclusion limits for the $(\tilde{W},\tilde{H})$ models. The limits are projected on to a two-dimensional plane as a function of the wino/higgsino mass parameters: $(M_2,\mu)$. For the limits shown on the $(M_2,\mu)$ plane, the excluded regions are indicated by the area inside the contours. The expected limits for the 1$\sigma$ down variation are not shown as no mass points could be excluded. The round excluded area in the top part corresponds to the excluded parameter space in the $(\tilde{W},~\tilde{H})$ model $(M_{2} > |\mu|)$, while the two small areas in at the bottom are that in the $(\tilde{H},~\tilde{W})$ model $(M_{2} < |\mu|)$.

95% CL exclusion limits for the $(\tilde{W},\tilde{H})$ models. The limits are projected on to a two-dimensional plane as a function of the wino/higgsino mass parameters: $(M_2,\mu)$. For the limits shown on the $(M_2,\mu)$ plane, the excluded regions are indicated by the area inside the contours. The round excluded area in the top part corresponds to the excluded parameter space in the $(\tilde{W},~\tilde{H})$ model $(M_{2} > |\mu|)$, while the two small areas in at the bottom are that in the $(\tilde{H},~\tilde{W})$ model $(M_{2} < |\mu|)$.

95% CL exclusion limits for the $(\tilde{W},\tilde{H})$ models. The limits are projected on to a two-dimensional plane as a function of the wino/higgsino mass parameters: $(M_2,\mu)$. For the limits shown on the $(M_2,\mu)$ plane, the excluded regions are indicated by the area inside the contours. The expected limits for the 1$\sigma$ down variation are not shown as no mass points could be excluded. The round excluded area in the top part corresponds to the excluded parameter space in the $(\tilde{W},~\tilde{H})$ model $(M_{2} > |\mu|)$, while the two small areas in at the bottom are that in the $(\tilde{H},~\tilde{W})$ model $(M_{2} < |\mu|)$.

95% CL exclusion limits for the $(\tilde{W},\tilde{H})$ models. The limits are projected on to a two-dimensional plane as a function of the wino/higgsino mass parameters: $(M_2,\mu)$. For the limits shown on the $(M_2,\mu)$ plane, the excluded regions are indicated by the area inside the contours. The expected limits for the 1$\sigma$ down variation are not shown as no mass points could be excluded. The round excluded area in the top part corresponds to the excluded parameter space in the $(\tilde{W},~\tilde{H})$ model $(M_{2} > |\mu|)$, while the two small areas in at the bottom are that in the $(\tilde{H},~\tilde{W})$ model $(M_{2} < |\mu|)$.

95% CL exclusion limits for the $(\tilde{H},\tilde{W})$ models. The limits are projected on to a two-dimensional plane as a function of the wino/higgsino mass parameters: $(M_2,\mu)$. For the limits shown on the $(M_2,\mu)$ plane, the excluded regions are indicated by the area inside the contours. The round excluded area in the top part corresponds to the excluded parameter space in the $(\tilde{W},~\tilde{H})$ model $(M_{2} > |\mu|)$, while the two small areas in at the bottom are that in the $(\tilde{H},~\tilde{W})$ model $(M_{2} < |\mu|)$.

95% CL exclusion limits for the $(\tilde{H},\tilde{W})$ models. The limits are projected on to a two-dimensional plane as a function of the wino/higgsino mass parameters: $(M_2,\mu)$. For the limits shown on the $(M_2,\mu)$ plane, the excluded regions are indicated by the area inside the contours. The expected limits for the 1$\sigma$ down variation are not shown as no mass points could be excluded. The round excluded area in the top part corresponds to the excluded parameter space in the $(\tilde{W},~\tilde{H})$ model $(M_{2} > |\mu|)$, while the two small areas in at the bottom are that in the $(\tilde{H},~\tilde{W})$ model $(M_{2} < |\mu|)$.

95% CL exclusion limits for the $(\tilde{H},\tilde{W})$ models. The limits are projected on to a two-dimensional plane as a function of the wino/higgsino mass parameters: $(M_2,\mu)$. For the limits shown on the $(M_2,\mu)$ plane, the excluded regions are indicated by the area inside the contours. The round excluded area in the top part corresponds to the excluded parameter space in the $(\tilde{W},~\tilde{H})$ model $(M_{2} > |\mu|)$, while the two small areas in at the bottom are that in the $(\tilde{H},~\tilde{W})$ model $(M_{2} < |\mu|)$.

95% CL exclusion limits for the $(\tilde{H},\tilde{W})$ models. The limits are projected on to a two-dimensional plane as a function of the wino/higgsino mass parameters: $(M_2,\mu)$. For the limits shown on the $(M_2,\mu)$ plane, the excluded regions are indicated by the area inside the contours. The expected limits for the 1$\sigma$ down variation are not shown as no mass points could be excluded. The round excluded area in the top part corresponds to the excluded parameter space in the $(\tilde{W},~\tilde{H})$ model $(M_{2} > |\mu|)$, while the two small areas in at the bottom are that in the $(\tilde{H},~\tilde{W})$ model $(M_{2} < |\mu|)$.

95% CL exclusion limits for the $(\tilde{H},\tilde{W})$ models. The limits are projected on to a two-dimensional plane as a function of the wino/higgsino mass parameters: $(M_2,\mu)$. For the limits shown on the $(M_2,\mu)$ plane, the excluded regions are indicated by the area inside the contours. The expected limits for the 1$\sigma$ down variation are not shown as no mass points could be excluded. The round excluded area in the top part corresponds to the excluded parameter space in the $(\tilde{W},~\tilde{H})$ model $(M_{2} > |\mu|)$, while the two small areas in at the bottom are that in the $(\tilde{H},~\tilde{W})$ model $(M_{2} < |\mu|)$.

Expected (dashed) and observed (solid red) 95% CL exclusion limit derived for the $(\tilde{H},\tilde{G})$ model, as a function of the lightest higgsino mass ($m(\tilde{\chi}_{1}^{0})$) and the branching ratio $\mathcal{B}(\tilde{\chi}_{1}^{0} \to Z\tilde{G}) (=1-\mathcal{B}(\tilde{\chi}_{1}^{0} \to h\tilde{G}))$. The excluded region is indicated by the area inside the contour.

Expected (dashed) and observed (solid red) 95% CL exclusion limit derived for the $(\tilde{H},\tilde{G})$ model, as a function of the lightest higgsino mass ($m(\tilde{\chi}_{1}^{0})$) and the branching ratio $\mathcal{B}(\tilde{\chi}_{1}^{0} \to Z\tilde{G}) (=1-\mathcal{B}(\tilde{\chi}_{1}^{0} \to h\tilde{G}))$. The excluded region is indicated by the area inside the contour.

Expected (dashed) and observed (solid red) 95% CL exclusion limit derived for the $(\tilde{H},\tilde{G})$ model, as a function of the lightest higgsino mass ($m(\tilde{\chi}_{1}^{0})$) and the branching ratio $\mathcal{B}(\tilde{\chi}_{1}^{0} \to Z\tilde{G}) (=1-\mathcal{B}(\tilde{\chi}_{1}^{0} \to h\tilde{G}))$. The excluded region is indicated by the area inside the contour.

Expected (dashed) and observed (solid red) 95% CL exclusion limit derived for the $(\tilde{H},\tilde{G})$ model, as a function of the lightest higgsino mass ($m(\tilde{\chi}_{1}^{0})$) and the branching ratio $\mathcal{B}(\tilde{\chi}_{1}^{0} \to Z\tilde{G}) (=1-\mathcal{B}(\tilde{\chi}_{1}^{0} \to h\tilde{G}))$. The excluded region is indicated by the area inside the contour.

Expected (dashed) and observed (solid red) 95% CL exclusion limit derived for the $(\tilde{H},\tilde{G})$ model, as a function of the lightest higgsino mass ($m(\tilde{\chi}_{1}^{0})$) and the branching ratio $\mathcal{B}(\tilde{\chi}_{1}^{0} \to Z\tilde{G}) (=1-\mathcal{B}(\tilde{\chi}_{1}^{0} \to h\tilde{G}))$. The excluded region is indicated by the area inside the contour.

Expected (dashed) and observed (solid red) 95% CL exclusion limit derived for the $(\tilde{H},\tilde{G})$ model, as a function of the lightest higgsino mass ($m(\tilde{\chi}_{1}^{0})$) and the branching ratio $\mathcal{B}(\tilde{\chi}_{1}^{0} \to Z\tilde{G}) (=1-\mathcal{B}(\tilde{\chi}_{1}^{0} \to h\tilde{G}))$. The excluded region is indicated by the area inside the contour.

95% CL exclusion limits for the $(\tilde{H},\tilde{a})$ model as the function of axino mass ($m(\tilde{a})$) and the lightest higgsino ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed lines) and observed (solid lines) limits with various $\mathcal{B}(\tilde{\chi}_{1}^{0} \to Z\tilde{a}) (=1-\mathcal{B}(\tilde{\chi}_{1}^{0} \to h\tilde{a}))$ hypotheses. No expected limit is derived for the case with $\mathcal{B}(\tilde{\chi}_{1}^{0} \to Z\tilde{a})=100$% as no mass point on the plane can be excluded.

95% CL exclusion limits for the $(\tilde{H},\tilde{a})$ model as the function of axino mass ($m(\tilde{a})$) and the lightest higgsino ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed line) and observed (solid red line) limits calculated for $\mathcal{B}(\tilde{\chi}_{1}^{0} \to Z\tilde{a})=100$%.

95% CL exclusion limits for the $(\tilde{H},\tilde{a})$ model as the function of axino mass ($m(\tilde{a})$) and the lightest higgsino ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed line) and observed (solid red line) limits calculated for $\mathcal{B}(\tilde{\chi}_{1}^{0} \to Z\tilde{a})=100$%.

95% CL exclusion limits for the $(\tilde{H},\tilde{a})$ model as the function of axino mass ($m(\tilde{a})$) and the lightest higgsino ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed lines) and observed (solid lines) limits with various $\mathcal{B}(\tilde{\chi}_{1}^{0} \to Z\tilde{a}) (=1-\mathcal{B}(\tilde{\chi}_{1}^{0} \to h\tilde{a}))$ hypotheses. No expected limit is derived for the case with $\mathcal{B}(\tilde{\chi}_{1}^{0} \to Z\tilde{a})=100$% as no mass point on the plane can be excluded.

95% CL exclusion limits for the $(\tilde{H},\tilde{a})$ model as the function of axino mass ($m(\tilde{a})$) and the lightest higgsino ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed line) and observed (solid red line) limits calculated for $\mathcal{B}(\tilde{\chi}_{1}^{0} \to Z\tilde{a})=100$%.

95% CL exclusion limits for the $(\tilde{H},\tilde{a})$ model as the function of axino mass ($m(\tilde{a})$) and the lightest higgsino ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed line) and observed (solid red line) limits calculated for $\mathcal{B}(\tilde{\chi}_{1}^{0} \to Z\tilde{a})=100$%.

95% CL exclusion limits for the $(\tilde{H},\tilde{a})$ model as the function of axino mass ($m(\tilde{a})$) and the lightest higgsino ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed lines) and observed (solid lines) limits with various $\mathcal{B}(\tilde{\chi}_{1}^{0} \to Z\tilde{a}) (=1-\mathcal{B}(\tilde{\chi}_{1}^{0} \to h\tilde{a}))$ hypotheses. No expected limit is derived for the case with $\mathcal{B}(\tilde{\chi}_{1}^{0} \to Z\tilde{a})=75$% as no mass point on the plane can be excluded.

95% CL exclusion limits for the $(\tilde{H},\tilde{a})$ model as the function of axino mass ($m(\tilde{a})$) and the lightest higgsino ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed lines) and observed (solid lines) limits with various $\mathcal{B}(\tilde{\chi}_{1}^{0} \to Z\tilde{a}) (=1-\mathcal{B}(\tilde{\chi}_{1}^{0} \to h\tilde{a}))$ hypotheses. No expected limit is derived for the case with $\mathcal{B}(\tilde{\chi}_{1}^{0} \to Z\tilde{a})=75$% as no mass point on the plane can be excluded.

95% CL exclusion limits for the $(\tilde{H},\tilde{a})$ model as the function of axino mass ($m(\tilde{a})$) and the lightest higgsino ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed lines) and observed (solid lines) limits with various $\mathcal{B}(\tilde{\chi}_{1}^{0} \to Z\tilde{a}) (=1-\mathcal{B}(\tilde{\chi}_{1}^{0} \to h\tilde{a}))$ hypotheses. No expected limit is derived for the case with $\mathcal{B}(\tilde{\chi}_{1}^{0} \to Z\tilde{a})=50$% as no mass point on the plane can be excluded.

95% CL exclusion limits for the $(\tilde{H},\tilde{a})$ model as the function of axino mass ($m(\tilde{a})$) and the lightest higgsino ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed lines) and observed (solid lines) limits with various $\mathcal{B}(\tilde{\chi}_{1}^{0} \to Z\tilde{a}) (=1-\mathcal{B}(\tilde{\chi}_{1}^{0} \to h\tilde{a}))$ hypotheses. No expected limit is derived for the case with $\mathcal{B}(\tilde{\chi}_{1}^{0} \to Z\tilde{a})=50$% as no mass point on the plane can be excluded.

95% CL exclusion limits for the $(\tilde{H},\tilde{a})$ model as the function of axino mass ($m(\tilde{a})$) and the lightest higgsino ($m(\tilde{\chi}_{1}^{0})$). Expected (dashed lines) and observed (solid lines) limits with various $\mathcal{B}(\tilde{\chi}_{1}^{0} \to Z\tilde{a}) (=1-\mathcal{B}(\tilde{\chi}_{1}^{0} \to h\tilde{a}))$ hypotheses. No expected limit is derived for the case with $\mathcal{B}(\tilde{\chi}_{1}^{0} \to Z\tilde{a})=25$% as no mass point on the plane can be excluded.

The $\tilde{\chi}_{\textrm{heavy}}$ branching ratios in the $(\tilde{W},\tilde{H})$ model ($\tan\beta=10, \mu>0$). The branching ratios of wino-like chargino ($\tilde{\chi}_{2}^{\pm}$) and wino-like neutralino ($\tilde{\chi}_{3}^{0}$) are shown as the function of the mass of $\tilde{\chi}_{2}^{\pm}$ and that of the lightest higgsino-like neutralino ($\tilde{\chi}_{1}^{0}$), representing $m(\tilde{\chi}_{\textrm{light}})$ and $m(\tilde{\chi}_{\textrm{heavy}})$ respectively. The branchings into the two neutral higgsinos are summed up in the presentation i.e. $\mathcal{B}(\dots \rightarrow \tilde{\chi}_{1,2}^{0}) := \mathcal{B}(\dots \rightarrow \tilde{\chi}_{1}^{0})+\mathcal{B}(\dots \rightarrow \tilde{\chi}_{2}^{0})$.

The $\tilde{\chi}_{\textrm{heavy}}$ branching ratios in the $(\tilde{W},\tilde{H})$ model ($\tan\beta=10, \mu>0$). The branching ratios of wino-like chargino ($\tilde{\chi}_{2}^{\pm}$) and wino-like neutralino ($\tilde{\chi}_{3}^{0}$) are shown as the function of the mass of $\tilde{\chi}_{2}^{\pm}$ and that of the lightest higgsino-like neutralino ($\tilde{\chi}_{1}^{0}$), representing $m(\tilde{\chi}_{\textrm{light}})$ and $m(\tilde{\chi}_{\textrm{heavy}})$ respectively. The branchings into the two neutral higgsinos are summed up in the presentation i.e. $\mathcal{B}(\dots \rightarrow \tilde{\chi}_{1,2}^{0}) := \mathcal{B}(\dots \rightarrow \tilde{\chi}_{1}^{0})+\mathcal{B}(\dots \rightarrow \tilde{\chi}_{2}^{0})$.

The $\tilde{\chi}_{\textrm{heavy}}$ branching ratios in the $(\tilde{W},\tilde{H})$ model ($\tan\beta=10, \mu>0$). The branching ratios of wino-like chargino ($\tilde{\chi}_{2}^{\pm}$) and wino-like neutralino ($\tilde{\chi}_{3}^{0}$) are shown as the function of the mass of $\tilde{\chi}_{2}^{\pm}$ and that of the lightest higgsino-like neutralino ($\tilde{\chi}_{1}^{0}$), representing $m(\tilde{\chi}_{\textrm{light}})$ and $m(\tilde{\chi}_{\textrm{heavy}})$ respectively. The branchings into the two neutral higgsinos are summed up in the presentation i.e. $\mathcal{B}(\dots \rightarrow \tilde{\chi}_{1,2}^{0}) := \mathcal{B}(\dots \rightarrow \tilde{\chi}_{1}^{0})+\mathcal{B}(\dots \rightarrow \tilde{\chi}_{2}^{0})$.

The $\tilde{\chi}_{\textrm{heavy}}$ branching ratios in the $(\tilde{W},\tilde{H})$ model ($\tan\beta=10, \mu>0$). The branching ratios of wino-like chargino ($\tilde{\chi}_{2}^{\pm}$) and wino-like neutralino ($\tilde{\chi}_{3}^{0}$) are shown as the function of the mass of $\tilde{\chi}_{2}^{\pm}$ and that of the lightest higgsino-like neutralino ($\tilde{\chi}_{1}^{0}$), representing $m(\tilde{\chi}_{\textrm{light}})$ and $m(\tilde{\chi}_{\textrm{heavy}})$ respectively. The branchings into the two neutral higgsinos are summed up in the presentation i.e. $\mathcal{B}(\dots \rightarrow \tilde{\chi}_{1,2}^{0}) := \mathcal{B}(\dots \rightarrow \tilde{\chi}_{1}^{0})+\mathcal{B}(\dots \rightarrow \tilde{\chi}_{2}^{0})$.

The $\tilde{\chi}_{\textrm{heavy}}$ branching ratios in the $(\tilde{W},\tilde{H})$ model ($\tan\beta=10, \mu>0$). The branching ratios of wino-like chargino ($\tilde{\chi}_{2}^{\pm}$) and wino-like neutralino ($\tilde{\chi}_{3}^{0}$) are shown as the function of the mass of $\tilde{\chi}_{2}^{\pm}$ and that of the lightest higgsino-like neutralino ($\tilde{\chi}_{1}^{0}$), representing $m(\tilde{\chi}_{\textrm{light}})$ and $m(\tilde{\chi}_{\textrm{heavy}})$ respectively. The branchings into the two neutral higgsinos are summed up in the presentation i.e. $\mathcal{B}(\dots \rightarrow \tilde{\chi}_{1,2}^{0}) := \mathcal{B}(\dots \rightarrow \tilde{\chi}_{1}^{0})+\mathcal{B}(\dots \rightarrow \tilde{\chi}_{2}^{0})$.

The $\tilde{\chi}_{\textrm{heavy}}$ branching ratios in the $(\tilde{W},\tilde{H})$ model ($\tan\beta=10, \mu>0$). The branching ratios of wino-like chargino ($\tilde{\chi}_{2}^{\pm}$) and wino-like neutralino ($\tilde{\chi}_{3}^{0}$) are shown as the function of the mass of $\tilde{\chi}_{2}^{\pm}$ and that of the lightest higgsino-like neutralino ($\tilde{\chi}_{1}^{0}$), representing $m(\tilde{\chi}_{\textrm{light}})$ and $m(\tilde{\chi}_{\textrm{heavy}})$ respectively. The branchings into the two neutral higgsinos are summed up in the presentation i.e. $\mathcal{B}(\dots \rightarrow \tilde{\chi}_{1,2}^{0}) := \mathcal{B}(\dots \rightarrow \tilde{\chi}_{1}^{0})+\mathcal{B}(\dots \rightarrow \tilde{\chi}_{2}^{0})$.

The $\tilde{\chi}_{\textrm{heavy}}$ branching ratios in the $(\tilde{H},\tilde{W})$ model ($\tan\beta=10, \mu>0$). The branching ratios of higgsino-like chargino ($\tilde{\chi}_{2}^{\pm}$) and higgsino-like neutralinos ($\tilde{\chi}_{1}^{0}$, $\tilde{\chi}_{3}^{0}$) as the function of the mass of $\tilde{\chi}_{2}^{\pm}$ and that of wino-like neutralino ($\tilde{\chi}_{1}^{0}$), representing $m(\tilde{\chi}_{\textrm{light}})$ and $m(\tilde{\chi}_{\textrm{heavy}})$ respectively.

The $\tilde{\chi}_{\textrm{heavy}}$ branching ratios in the $(\tilde{H},\tilde{W})$ model ($\tan\beta=10, \mu>0$). The branching ratios of higgsino-like chargino ($\tilde{\chi}_{2}^{\pm}$) and higgsino-like neutralinos ($\tilde{\chi}_{1}^{0}$, $\tilde{\chi}_{3}^{0}$) as the function of the mass of $\tilde{\chi}_{2}^{\pm}$ and that of wino-like neutralino ($\tilde{\chi}_{1}^{0}$), representing $m(\tilde{\chi}_{\textrm{light}})$ and $m(\tilde{\chi}_{\textrm{heavy}})$ respectively.

The $\tilde{\chi}_{\textrm{heavy}}$ branching ratios in the $(\tilde{H},\tilde{W})$ model ($\tan\beta=10, \mu>0$). The branching ratios of higgsino-like chargino ($\tilde{\chi}_{2}^{\pm}$) and higgsino-like neutralinos ($\tilde{\chi}_{1}^{0}$, $\tilde{\chi}_{3}^{0}$) as the function of the mass of $\tilde{\chi}_{2}^{\pm}$ and that of wino-like neutralino ($\tilde{\chi}_{1}^{0}$), representing $m(\tilde{\chi}_{\textrm{light}})$ and $m(\tilde{\chi}_{\textrm{heavy}})$ respectively.

The $\tilde{\chi}_{\textrm{heavy}}$ branching ratios in the $(\tilde{H},\tilde{W})$ model ($\tan\beta=10, \mu>0$). The branching ratios of higgsino-like chargino ($\tilde{\chi}_{2}^{\pm}$) and higgsino-like neutralinos ($\tilde{\chi}_{1}^{0}$, $\tilde{\chi}_{3}^{0}$) as the function of the mass of $\tilde{\chi}_{2}^{\pm}$ and that of wino-like neutralino ($\tilde{\chi}_{1}^{0}$), representing $m(\tilde{\chi}_{\textrm{light}})$ and $m(\tilde{\chi}_{\textrm{heavy}})$ respectively.

The $\tilde{\chi}_{\textrm{heavy}}$ branching ratios in the $(\tilde{H},\tilde{W})$ model ($\tan\beta=10, \mu>0$). The branching ratios of higgsino-like chargino ($\tilde{\chi}_{2}^{\pm}$) and higgsino-like neutralinos ($\tilde{\chi}_{1}^{0}$, $\tilde{\chi}_{3}^{0}$) as the function of the mass of $\tilde{\chi}_{2}^{\pm}$ and that of wino-like neutralino ($\tilde{\chi}_{1}^{0}$), representing $m(\tilde{\chi}_{\textrm{light}})$ and $m(\tilde{\chi}_{\textrm{heavy}})$ respectively.

The $\tilde{\chi}_{\textrm{heavy}}$ branching ratios in the $(\tilde{H},\tilde{W})$ model ($\tan\beta=10, \mu>0$). The branching ratios of higgsino-like chargino ($\tilde{\chi}_{2}^{\pm}$) and higgsino-like neutralinos ($\tilde{\chi}_{1}^{0}$, $\tilde{\chi}_{3}^{0}$) as the function of the mass of $\tilde{\chi}_{2}^{\pm}$ and that of wino-like neutralino ($\tilde{\chi}_{1}^{0}$), representing $m(\tilde{\chi}_{\textrm{light}})$ and $m(\tilde{\chi}_{\textrm{heavy}})$ respectively.

The $\tilde{\chi}_{\textrm{heavy}}$ branching ratios in the $(\tilde{H},\tilde{W})$ model ($\tan\beta=10, \mu>0$). The branching ratios of higgsino-like chargino ($\tilde{\chi}_{2}^{\pm}$) and higgsino-like neutralinos ($\tilde{\chi}_{1}^{0}$, $\tilde{\chi}_{3}^{0}$) as the function of the mass of $\tilde{\chi}_{2}^{\pm}$ and that of wino-like neutralino ($\tilde{\chi}_{1}^{0}$), representing $m(\tilde{\chi}_{\textrm{light}})$ and $m(\tilde{\chi}_{\textrm{heavy}})$ respectively.

The $\tilde{\chi}_{\textrm{heavy}}$ branching ratios in the $(\tilde{H},\tilde{W})$ model ($\tan\beta=10, \mu>0$). The branching ratios of higgsino-like chargino ($\tilde{\chi}_{2}^{\pm}$) and higgsino-like neutralinos ($\tilde{\chi}_{1}^{0}$, $\tilde{\chi}_{3}^{0}$) as the function of the mass of $\tilde{\chi}_{2}^{\pm}$ and that of wino-like neutralino ($\tilde{\chi}_{1}^{0}$), representing $m(\tilde{\chi}_{\textrm{light}})$ and $m(\tilde{\chi}_{\textrm{heavy}})$ respectively.

The $\tilde{\chi}_{\textrm{heavy}}$ branching ratios in the $(\tilde{H},\tilde{W})$ model ($\tan\beta=10, \mu>0$). The branching ratios of higgsino-like chargino ($\tilde{\chi}_{2}^{\pm}$) and higgsino-like neutralinos ($\tilde{\chi}_{1}^{0}$, $\tilde{\chi}_{3}^{0}$) as the function of the mass of $\tilde{\chi}_{2}^{\pm}$ and that of wino-like neutralino ($\tilde{\chi}_{1}^{0}$), representing $m(\tilde{\chi}_{\textrm{light}})$ and $m(\tilde{\chi}_{\textrm{heavy}})$ respectively.

Expected (dashed) and observed (solid) 95% CL exclusion limits on $(\tilde{W},~\tilde{B})$-SIM model (C1C1-WW). The black numbers represents the expected cross-section upper-limits.

Expected (dashed) and observed (solid) 95% CL exclusion limits on $(\tilde{W},~\tilde{B})$-SIM model (C1N2-WZ). The black numbers represents the expected cross-section upper-limits.

Expected (dashed) and observed (solid) 95% CL exclusion limits on $(\tilde{W},~\tilde{B})$-SIM model (C1N2-Wh). The black numbers represents the expected cross-section upper-limits.

Expected (dashed) and observed (solid) 95% CL exclusion limits on $(\tilde{H},\tilde{G})$ models. The black numbers represents the expected cross-section upper-limits.

Expected (dashed) and observed (solid) 95% CL exclusion limits on $(\tilde{W},~\tilde{B})$-SIM model (C1C1-WW). The black numbers represents the observed cross-section upper-limits.

Expected (dashed) and observed (solid) 95% CL exclusion limits on $(\tilde{W},~\tilde{B})$-SIM model (C1N2-WZ). The black numbers represents the observed cross-section upper-limits.

Expected (dashed) and observed (solid) 95% CL exclusion limits on $(\tilde{W},~\tilde{B})$-SIM model (C1N2-Wh). The black numbers represents the observed cross-section upper-limits.

Expected (dashed) and observed (solid) 95% CL exclusion limits on $(\tilde{H},\tilde{G})$ models. The black numbers represents the observed cross-section upper-limits.

Signal acceptance of $(\tilde{W},\tilde{B})$ simplified models (C1C1-WW) by their most relevant SRs, evaluated using MC simulation. The acceptance is given by the ratio of weighted selected events by the SR to the weighted total generated events including all the $W/Z/h$ decays. The selection is based on generator-level particle information. The efficiency of lepton reconstruction/identification, $b$-tagging, as well as the $D_2$ and $n_{\textrm{trk}}$ selection in the $W_{qq}$/$Z_{qq}$-tagging are treated as 100%.

Signal acceptance of $(\tilde{W},\tilde{B})$ simplified models (C1N2-WZ) by their most relevant SRs, evaluated using MC simulation. The acceptance is given by the ratio of weighted selected events by the SR to the weighted total generated events including all the $W/Z/h$ decays. The selection is based on generator-level particle information. The efficiency of lepton reconstruction/identification, $b$-tagging, as well as the $D_2$ and $n_{\textrm{trk}}$ selection in the $W_{qq}$/$Z_{qq}$-tagging are treated as 100%.

Signal acceptance of $(\tilde{W},\tilde{B})$ simplified models (C1N2-WZ) by their most relevant SRs, evaluated using MC simulation. The acceptance is given by the ratio of weighted selected events by the SR to the weighted total generated events including all the $W/Z/h$ decays. The selection is based on generator-level particle information. The efficiency of lepton reconstruction/identification, $b$-tagging, as well as the $D_2$ and $n_{\textrm{trk}}$ selection in the $W_{qq}$/$Z_{qq}$-tagging are treated as 100%.

Signal acceptance of $(\tilde{W},\tilde{B})$ simplified models (C1N2-Wh) by their most relevant SRs, evaluated using MC simulation. The acceptance is given by the ratio of weighted selected events by the SR to the weighted total generated events including all the $W/Z/h$ decays. The selection is based on generator-level particle information. The efficiency of lepton reconstruction/identification, $b$-tagging, as well as the $D_2$ and $n_{\textrm{trk}}$ selection in the $W_{qq}$/$Z_{qq}$-tagging are treated as 100%.

Signal acceptance of $(\tilde{H},\tilde{B})$ simplified models (N2N3-ZZ) by their most relevant SRs, evaluated using MC simulation. The acceptance is given by the ratio of weighted selected events by the SR to the weighted total generated events including all the $W/Z/h$ decays. The selection is based on generator-level particle information. The efficiency of lepton reconstruction/identification, $b$-tagging, as well as the $D_2$ and $n_{\textrm{trk}}$ selection in the $W_{qq}$/$Z_{qq}$-tagging are treated as 100%. Acceptance below 0.005\% is rounded to 0.00 in the entry.

Signal acceptance of $(\tilde{H},\tilde{B})$ simplified models (N2N3-ZZ) by their most relevant SRs, evaluated using MC simulation. The acceptance is given by the ratio of weighted selected events by the SR to the weighted total generated events including all the $W/Z/h$ decays. The selection is based on generator-level particle information. The efficiency of lepton reconstruction/identification, $b$-tagging, as well as the $D_2$ and $n_{\textrm{trk}}$ selection in the $W_{qq}$/$Z_{qq}$-tagging are treated as 100%. Acceptance below 0.005\% is rounded to 0.00 in the entry.

Signal acceptance of $(\tilde{H},\tilde{B})$ simplified models (N2N3-Zh) by their most relevant SRs, evaluated using MC simulation. The acceptance is given by the ratio of weighted selected events by the SR to the weighted total generated events including all the $W/Z/h$ decays. The selection is based on generator-level particle information. The efficiency of lepton reconstruction/identification, $b$-tagging, as well as the $D_2$ and $n_{\textrm{trk}}$ selection in the $W_{qq}$/$Z_{qq}$-tagging are treated as 100%. Acceptance below 0.005\% is rounded to 0.00 in the entry.

Signal acceptance of $(\tilde{H},\tilde{B})$ simplified models (N2N3-hh) by their most relevant SRs, evaluated using MC simulation. The acceptance is given by the ratio of weighted selected events by the SR to the weighted total generated events including all the $W/Z/h$ decays. The selection is based on generator-level particle information. The efficiency of lepton reconstruction/identification, $b$-tagging, as well as the $D_2$ and $n_{\textrm{trk}}$ selection in the $W_{qq}$/$Z_{qq}$-tagging are treated as 100%. Acceptance below 0.005\% is rounded to 0.00 in the entry.

Signal acceptance of the $(\tilde{H},\tilde{G})$ model by SR-4Q-VV, evaluated using MC simulation. The acceptance is given by the ratio of weighted selected events by the SR to the weighted total generated events including all the $W/Z/h$ decays. The selection is based on generator-level particle information. The efficiency of lepton reconstruction/identification, $b$-tagging, as well as the $D_2$ and $n_{\textrm{trk}}$ selection in the $W_{qq}$/$Z_{qq}$-tagging are treated as 100%. Acceptance below 0.005\% is rounded to 0.00 in the entry.

Signal acceptance of the $(\tilde{H},\tilde{G})$ model by SR-2B2Q-VZ, evaluated using MC simulation. The acceptance is given by the ratio of weighted selected events by the SR to the weighted total generated events including all the $W/Z/h$ decays. The selection is based on generator-level particle information. The efficiency of lepton reconstruction/identification, $b$-tagging, as well as the $D_2$ and $n_{\textrm{trk}}$ selection in the $W_{qq}$/$Z_{qq}$-tagging are treated as 100%. Acceptance below 0.005\% is rounded to 0.00 in the entry.

Signal acceptance of the $(\tilde{H},\tilde{G})$ model by SR-2B2Q-Vh, evaluated using MC simulation. The acceptance is given by the ratio of weighted selected events by the SR to the weighted total generated events including all the $W/Z/h$ decays. The selection is based on generator-level particle information. The efficiency of lepton reconstruction/identification, $b$-tagging, as well as the $D_2$ and $n_{\textrm{trk}}$ selection in the $W_{qq}$/$Z_{qq}$-tagging are treated as 100%. Acceptance below 0.005\% is rounded to 0.00 in the entry.

Efficiency for $(\tilde{W},\tilde{B})$ simplified models (C1C1-WW) in their most relevant SRs. The efficiency in a given SR is defined by the ratio of weighted events selected based on the generator-level particle information and that based on detector simulation and particle reconstruction. This mainly accounts for the efficiency of lepton reconstruction/identification, $b$-tagging, as well as the $D_2$ and $n_{\textrm{trk}}$ selection in the and $W_{qq}$/$Z_{qq}$-tagging.

Efficiency for $(\tilde{W},\tilde{B})$ simplified models (C1N2-WZ) in their most relevant SRs. The efficiency in a given SR is defined by the ratio of weighted events selected based on the generator-level particle information and that based on detector simulation and particle reconstruction. This mainly accounts for the efficiency of lepton reconstruction/identification, $b$-tagging, as well as the $D_2$ and $n_{\textrm{trk}}$ selection in the and $W_{qq}$/$Z_{qq}$-tagging.

Efficiency for $(\tilde{W},\tilde{B})$ simplified models (C1N2-WZ) in their most relevant SRs. The efficiency in a given SR is defined by the ratio of weighted events selected based on the generator-level particle information and that based on detector simulation and particle reconstruction. This mainly accounts for the efficiency of lepton reconstruction/identification, $b$-tagging, as well as the $D_2$ and $n_{\textrm{trk}}$ selection in the and $W_{qq}$/$Z_{qq}$-tagging.

Efficiency for $(\tilde{W},\tilde{B})$ simplified models (C1N2-Wh) in their most relevant SRs. The efficiency in a given SR is defined by the ratio of weighted events selected based on the generator-level particle information and that based on detector simulation and particle reconstruction. This mainly accounts for the efficiency of lepton reconstruction/identification, $b$-tagging, as well as the $D_2$ and $n_{\textrm{trk}}$ selection in the and $W_{qq}$/$Z_{qq}$-tagging.

Efficiency for $(\tilde{H},\tilde{B})$ simplified models (N2N3-ZZ) in their most relevant SRs. The efficiency in a given SR is defined by the ratio of weighted events selected based on the generator-level particle information and that based on detector simulation and particle reconstruction. This mainly accounts for the efficiency of lepton reconstruction/identification, $b$-tagging, as well as the $D_2$ and $n_{\textrm{trk}}$ selection in the and $W_{qq}$/$Z_{qq}$-tagging. Efficiency below 0.005\% is rounded to 0.00 in the entry.

Efficiency for $(\tilde{H},\tilde{B})$ simplified models (N2N3-ZZ) in their most relevant SRs. The efficiency in a given SR is defined by the ratio of weighted events selected based on the generator-level particle information and that based on detector simulation and particle reconstruction. This mainly accounts for the efficiency of lepton reconstruction/identification, $b$-tagging, as well as the $D_2$ and $n_{\textrm{trk}}$ selection in the and $W_{qq}$/$Z_{qq}$-tagging. Efficiency below 0.005\% is rounded to 0.00 in the entry.

Efficiency for $(\tilde{H},\tilde{B})$ simplified models (N2N3-Zh) in their most relevant SRs. The efficiency in a given SR is defined by the ratio of weighted events selected based on the generator-level particle information and that based on detector simulation and particle reconstruction. This mainly accounts for the efficiency of lepton reconstruction/identification, $b$-tagging, as well as the $D_2$ and $n_{\textrm{trk}}$ selection in the and $W_{qq}$/$Z_{qq}$-tagging. Efficiency below 0.005\% is rounded to 0.00 in the entry.

Efficiency for $(\tilde{H},\tilde{B})$ simplified models (N2N3-hh) in their most relevant SRs. The efficiency in a given SR is defined by the ratio of weighted events selected based on the generator-level particle information and that based on detector simulation and particle reconstruction. This mainly accounts for the efficiency of lepton reconstruction/identification, $b$-tagging, as well as the $D_2$ and $n_{\textrm{trk}}$ selection in the and $W_{qq}$/$Z_{qq}$-tagging. Efficiency below 0.005\% is rounded to 0.00 in the entry.

Efficiency for $(\tilde{H},\tilde{G})$ in SR-4Q-VV. The efficiency in a given SR is defined by the ratio of weighted events selected based on the generator-level particle information and that based on detector simulation and particle reconstruction. This mainly accounts for the efficiency of lepton reconstruction/identification, $b$-tagging, as well as the $D_2$ and $n_{\textrm{trk}}$ selection in the and $W_{qq}$/$Z_{qq}$-tagging. Efficiency below 0.005\% is rounded to 0.00 in the entry. The spiky efficiency values (e.g. $m(\tilde{\chi}_{1}^{0})=600~\textrm{GeV}$ in SR-4Q-VV) are because of the difference between the truth and reconstructed samples amplified by a statistical fluctuation due to the limited statistics.

Efficiency for $(\tilde{H},\tilde{G})$ in SR-2B2Q-VZ. The efficiency in a given SR is defined by the ratio of weighted events selected based on the generator-level particle information and that based on detector simulation and particle reconstruction. This mainly accounts for the efficiency of lepton reconstruction/identification, $b$-tagging, as well as the $D_2$ and $n_{\textrm{trk}}$ selection in the and $W_{qq}$/$Z_{qq}$-tagging. Efficiency below 0.005\% is rounded to 0.00 in the entry. The spiky efficiency values (e.g. $m(\tilde{\chi}_{1}^{0})=600~\textrm{GeV}$ in SR-4Q-VV) are because of the difference between the truth and reconstructed samples amplified by a statistical fluctuation due to the limited statistics.

Efficiency for $(\tilde{H},\tilde{G})$ in SR-2B2Q-Vh. The efficiency in a given SR is defined by the ratio of weighted events selected based on the generator-level particle information and that based on detector simulation and particle reconstruction. This mainly accounts for the efficiency of lepton reconstruction/identification, $b$-tagging, as well as the $D_2$ and $n_{\textrm{trk}}$ selection in the and $W_{qq}$/$Z_{qq}$-tagging. Efficiency below 0.005\% is rounded to 0.00 in the entry. The spiky efficiency values (e.g. $m(\tilde{\chi}_{1}^{0})=600~\textrm{GeV}$ in SR-4Q-VV) are because of the difference between the truth and reconstructed samples amplified by a statistical fluctuation due to the limited statistics.

Differential cross section as a function of $m_{\gamma\gamma}$. The table contains the values measured in data and theory predictions from SHERPA, DIPHOX and NNLOJET.

Differential cross section as a function of $p_{T,\gamma\gamma}$. The table contains the values measured in data and theory predictions from SHERPA, DIPHOX and NNLOJET.

Differential cross section as a function of $a_{T,\gamma\gamma}$. The table contains the values measured in data and theory predictions from SHERPA, DIPHOX and NNLOJET.

Differential cross section as a function of $\phi_{\eta}*$. The table contains the values measured in data and theory predictions from SHERPA, DIPHOX and NNLOJET.

Differential cross section as a function of $\pi-\Delta\phi_{\gamma\gamma}$. The table contains the values measured in data and theory predictions from SHERPA, DIPHOX and NNLOJET.

Differential cross section as a function of $|cos\theta*|^{(CS)}$. The table contains the values measured in data and theory predictions from SHERPA, DIPHOX and NNLOJET.

The contribution from different systematic uncertainties to the measured $t\bar{t}t\bar{t}$ production cross section, grouped in categories.

The results of the fitted signal strength $\mu$ in the 1L/2LOS and 2LSS/3L combined channel.

The results of fitted inclusive ${t\bar{t}t\bar{t}}$ cross-section in the 1L/2LOS and 2LSS/3L combined channel.

Comparison between data and prediction for the distribution of the sum of the pseudo-continuous b-tagging score over the six jets with the highest score in the 1L,$\geq$9j,$\geq$3b region before the fit.

Comparison between data and prediction for the distribution of the sum of the pseudo-continuous b-tagging score over the six jets with the highest score in the 1L,$\geq$9j,$\geq$3b region after the fit.

Comparison between data and prediction for the distribution of the sum of the pseudo-continuous b-tagging score over the six jets with the highest score in the 2LOS,$\geq$7j,$\geq$3b region before the fit.

Comparison between data and prediction for the distribution of the sum of the pseudo-continuous b-tagging score over the six jets with the highest score in the 2LOS,$\geq$7j,$\geq$3b region after the fit.

Comparison between data and prediction for the distribution of the scalar sum of all jet and lepton pT in the event in the 1L,$\geq$8j,$\geq$3b region before the fit.

Comparison between data and prediction for the distribution of the scalar sum of all jet and lepton pT in the event in the 1L,$\geq$8j,$\geq$3b region after the fit.

Comparison between data and prediction for the distribution of the scalar sum of all jet and lepton pT in the event in the 2LOS,$\geq$6j,$\geq$3b region before the fit.

Comparison between data and prediction for the distribution of the scalar sum of all jet and lepton pT in the event in the 2LOS,$\geq$6j,$\geq$3b region after the fit.

Comparison between data and prediction for the distribution of number of jets in the 1L,$\geq$8j,$\geq$3b region before the fit.

Comparison between data and prediction for the distribution of number of jets in the 1L,$\geq$8j,$\geq$3b region after the fit.

Comparison between data and prediction for the distribution of number of jets in the 2LOS,$\geq$6j,$\geq$3b region before the fit.

Comparison between data and prediction for the distribution of number of jets in the 2LOS,$\geq$6j,$\geq$3b region after the fit.

Comparison between data and prediction for the distribution of b-jets multiplicity in the 1L,$\geq$8j,$\geq$3b region before the fit.

Comparison between data and prediction for the distribution of b-jets multiplicity in the 1L,$\geq$8j,$\geq$3b region after the fit.

Comparison between data and prediction for the distribution of b-jets multiplicity in the 2LOS,$\geq$6j,$\geq$3b region before the fit.

Comparison between data and prediction for the distribution of b-jets multiplicity in the 2LOS,$\geq$6j,$\geq$3b region after the fit.

Comparison between data and prediction for the distribution of the BDT score in the 1L,9j,4b signal region before the fit.

Comparison between data and prediction for the distribution of the BDT score in the 1L,9j,4b signal region after the fit.

Comparison between data and prediction for the distribution of the BDT score in the 1L,9j,$\geq$5b signal region before the fit.

Comparison between data and prediction for the distribution of the BDT score in the 1L,9j,$\geq$5b signal region after the fit.

Comparison between data and prediction for the distribution of the BDT score in the 1L,$\geq$10j,3bL signal region before the fit.