Unfolded normalised differential Z+2j cross section as a function of the rapidity separation between the leading jets in the search region.

Unfolded normalised differential cross section distribution as a function of the number of jets in the rapidity interval between the two leading jets in the high mass region.

Unfolded normalised differential cross section distribution as a function of the normalised transverse momentum balance in the high mass region.

Unfolded normalised differential cross section distribution as a function of the azimuthal angle between the two leading jets in the high mass region.

Unfolded jet veto efficiency as a function of the dijet invariant mass in the baseline region.

Unfolded jet veto efficiency as a function of the rapidity separation between the two leading jets in the baseline region.

Unfolded average number of jets in the rapidity interval between the two leading jets as a function of the dijet invariant mass in the baseline region.

Unfolded average number of jets in the rapidity interval between the two leading jets as a function of the rapidity separation between the two leading jets in the baseline region.

Unfolded transverse momentum balance veto efficiency as a function of the dijet invariant mass in the baseline region.

Unfolded transverse momentum balance veto efficiency as a function of the rapidity separation between the two leading jets in the baseline region.

Unfolded normalised differential Z+2j cross section as a function of dijet invariant mass in the high-pt region.

Unfolded normalised differential Z+2j cross section as a function of dijet invariant mass in the control region.

Unfolded normalised differential Z+2j cross section as a function of the rapidity separation between the leading jets in the high-pt region.

Unfolded normalised differential Z+2j cross section as a function of the rapidity separation between the leading jets in the control region.

Unfolded jet veto efficiency as a function of the dijet invariant mass in the high-pt region.

Unfolded jet veto efficiency as a function of the rapidity separation between the two leading jets in the high-pt region.

Unfolded average number of jets in the rapidity interval between the two leading jets as a function of the dijet invariant mass in the high-pt region.

Unfolded average number of jets in the rapidity interval between the two leading jets as a function of the rapidity separation between the two leading jets in the high-pt region.

Unfolded transverse momentum balance veto efficiency as a function of the dijet invariant mass in the high-pt region.

Unfolded transverse momentum balance veto efficiency as a function of the rapidity separation between the two leading jets in the high-pt region.

The expected 95% CL exclusion contour (-1$\sigma$) for a simplified model of dark-matter production involving an axial-vector operator, Dirac DM and couplings $g_{q}$ = 0.25, $g_{\chi}$ = 1 and $g_{l}$ = 0 as a function of the dark-matter mass $m_{\chi}$ and the mediator mass $m_{\mathrm{med}}$. The plane under the limit curve is excluded.

The expected 95% CL exclusion contour for a simplified model of dark-matter production involving an axial-vector operator, Dirac DM and couplings $g_{q}$ = 0.25, $g_{\chi}$ = 1 and $g_{l}$ = 0 as a function of the dark-matter mass $m_{\chi}$ and the mediator mass $m_{\mathrm{med}}$. The plane under the limit curve is excluded.

The observed 95% CL exclusion contour for a simplified model of dark-matter production involving an axial-vector operator, Dirac DM and couplings $g_{q}$ = 0.1, $g_{\chi}$ = 1 and $g_{l}$ = 0.1 as a function of the dark-matter mass $m_{\chi}$ and the mediator mass $m_{\mathrm{med}}$. The plane under the limit curve is excluded.

The expected 95% CL exclusion contour (+1$\sigma$) for a simplified model of dark-matter production involving an axial-vector operator, Dirac DM and couplings $g_{q}$ = 0.1, $g_{\chi}$ = 1 and $g_{l}$ = 0.1 as a function of the dark-matter mass $m_{\chi}$ and the mediator mass $m_{\mathrm{med}}$. The plane under the limit curve is excluded.

The expected 95% CL exclusion contour (-1$\sigma$) for a simplified model of dark-matter production involving an axial-vector operator, Dirac DM and couplings $g_{q}$ = 0.1, $g_{\chi}$ = 1 and $g_{l}$ = 0.1 as a function of the dark-matter mass $m_{\chi}$ and the mediator mass $m_{\mathrm{med}}$. The plane under the limit curve is excluded.

The expected 95% CL exclusion contour for a simplified model of dark-matter production involving an axial-vector operator, Dirac DM and couplings $g_{q}$ = 0.1, $g_{\chi}$ = 1 and $g_{l}$ = 0.1 as a function of the dark-matter mass $m_{\chi}$ and the mediator mass $m_{\mathrm{med}}$. The plane under the limit curve is excluded.

The observed 95% CL exclusion contour for a simplified model of dark-matter production involving a vector operator with couplings $g_{q}$ = 0.25, $g_{\chi}$ =1 and $g_{l}$ = 0 as a function of the dark-matter mass $m_{\chi}$ and the mediator mass $m_{\mathrm{med}}$. The plane under the limit curve is excluded.

The expected 95% CL exclusion contour ($+1\sigma$) for a simplified model of dark-matter production involving a vector operator with couplings $g_{q}$ = 0.25, $g_{\chi}$ =1 and $g_{l}$ = 0 as a function of the dark-matter mass $m_{\chi}$ and the mediator mass $m_{\mathrm{med}}$. The plane under the limit curve is excluded.

The expected 95% CL exclusion contour ($-1\sigma$) for a simplified model of dark-matter production involving a vector operator with couplings $g_{q}$ = 0.25, $g_{\chi}$ =1 and $g_{l}$ = 0 as a function of the dark-matter mass $m_{\chi}$ and the mediator mass $m_{\mathrm{med}}$. The plane under the limit curve is excluded.

The expected 95% CL exclusion contour for a simplified model of dark-matter production involving a vector operator with couplings $g_{q}$ = 0.25, $g_{\chi}$ =1 and $g_{l}$ = 0 as a function of the dark-matter mass $m_{\chi}$ and the mediator mass $m_{\mathrm{med}}$. The plane under the limit curve is excluded.

The observed 95% CL exclusion contour for a simplified model of dark-matter production involving for a vector operator with couplings $g_{q}$ = 0.1, $g_{\chi}$ = 1 and $g_{l}$ = 0.01 as a function of the dark-matter mass $m_{\chi}$ and the mediator mass $m_{\mathrm{med}}$. The plane under the limit curve is excluded.

The expected 95% CL exclusion contour ($+1\sigma$) for a simplified model of dark-matter production involving for a vector operator with couplings $g_{q}$ = 0.1, $g_{\chi}$ = 1 and $g_{l}$ = 0.01 as a function of the dark-matter mass $m_{\chi}$ and the mediator mass $m_{\mathrm{med}}$. The plane under the limit curve is excluded.

The expected 95% CL exclusion contour ($-1\sigma$) for a simplified model of dark-matter production involving for a vector operator with couplings $g_{q}$ = 0.1, $g_{\chi}$ = 1 and $g_{l}$ = 0.01 as a function of the dark-matter mass $m_{\chi}$ and the mediator mass $m_{\mathrm{med}}$. The plane under the limit curve is excluded.

The expected 95% CL exclusion contour for a simplified model of dark-matter production involving for a vector operator with couplings $g_{q}$ = 0.1, $g_{\chi}$ = 1 and $g_{l}$ = 0.01 as a function of the dark-matter mass $m_{\chi}$ and the mediator mass $m_{\mathrm{med}}$. The plane under the limit curve is excluded.

The 90% CL exclusion limit on the $\chi$-proton scattering cross section in a simplifed model of dark-matter production involving an axial-vector operator, Dirac DM and couplings $g_{q}$ = 0.25, $g_{\chi}$ = 1 and $g_{l}$ = 0 as a function of the dark-matter mass $m_{\chi}$.

The 90% CL exclusion limit on the $\chi$-nucleon scattering cross section in a simplifed model of dark-matter production involving a vector operator, Dirac DM and couplings $g_{q}$ = 0.25, $g_{\chi}$ = 1 and $g_{l}$ = 0 as a function of the dark-matter mass $m_{\chi}$.

The observed and expected 95% CL limits on M* for a dimension-7 operator EFT model with a contact interaction of type $\gamma\gamma\chi\chi$ as a function of dark-matter mass $m_{\chi}$.

The observed and expected limit at 95% CL on the production cross section of a $Z\gamma$ resonance as a function of its mass.

The observed 95% CL upper limits on signal strength $\mu$, the ratio of the experimental limit to the predicted signal cross section, for a simplified model of dark matter production involving an axial-vector operator, Dirac DM and couplings $g_{q}$ = 0.25 and $g_{\chi}$ = 1 as a function of the DM and the mediator particle masses. The bound on $\mu$ only applies for choices of couplings that yield the same kinematic distributions as the benchmark model.

Acceptance, in %, for a simplified model of dark matter production involving an axial-vector operator, Dirac DM and couplings $g_{q}$= 0.25 and $g_{\chi}$ = 1 for various $m_{\chi}$ and $m_{\textrm{med}}$ values. It is constant as a function of $m_{\chi}$ for a fixed $m_{\textrm{med}}$ in the region $m_{\textrm{med}}>2m_{\chi}$.

Fiducial reconstruction efficiencies in the three inclusive signal regions for a simplified model of dark matter production involving an axial-vector operator, Dirac DM and couplings $g_{q}$= 0.25 and $g_{\chi}$ = 1 for various $m_{\chi}$ and $m_{\textrm{med}}$ values. It is constant as a function of $m_{\chi}$ for a fixed $m_{\textrm{med}}$ in the region $m_{\textrm{med}}>2m_{\chi}$.

Measured differential cross section with associated uncertainties as a function of absolute rapidity of diphoton system. Each systematic uncertainty sources 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 multiplicity of jets with transverse momentum pT(jet) > 30 GeV. Each systematic uncertainty sources 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 multiplicity of jets with transverse momentum pT(jet) > 30 GeV. Each systematic uncertainty sources 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 multiplicity of jets with transverse momentum pT(jet) > 30 GeV. Each systematic uncertainty sources 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 multiplicity of jets with transverse momentum pT(jet) > 30 GeV. Each systematic uncertainty sources 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 transverse momentum of the leading jet. Each systematic uncertainty sources 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 transverse momentum of the leading jet. Each systematic uncertainty sources 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 absolute rapidity of the leading jet. Each systematic uncertainty sources 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 absolute rapidity of the leading jet. Each systematic uncertainty sources 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 scalar transverse momentum sum of all jets. Each systematic uncertainty sources 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 scalar transverse momentum sum of all jets. Each systematic uncertainty sources 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 transverse momentum of second leading jet. Each systematic uncertainty sources 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 transverse momentum of second leading jet. Each systematic uncertainty sources 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 rapidity separation of leading two jets. Each systematic uncertainty sources 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 rapidity separation of leading two jets. Each systematic uncertainty sources 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 azimuthal angle between diphoton and dijet systems. Each systematic uncertainty sources 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 azimuthal angle between diphoton and dijet systems. Each systematic uncertainty sources 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 cosine of the decay angle in the Collins-Soper frame. Each systematic uncertainty sources 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 cosine of the decay angle in the Collins-Soper frame. Each systematic uncertainty sources 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 cosine of the decay angle in the Collins-Soper frame. Each systematic uncertainty sources 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 cosine of the decay angle in the Collins-Soper frame. Each systematic uncertainty sources 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 azimuthal angle between the two leading jets. Each systematic uncertainty sources 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 azimuthal angle between the two leading jets. Each systematic uncertainty sources 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 diphoton thrust pT. Each systematic uncertainty sources 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 diphoton thrust pT. Each systematic uncertainty sources 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 rapidity separation of the two photons. Each systematic uncertainty sources 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 rapidity separation of the two photons. Each systematic uncertainty sources 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 tau of highest-tau jet (see paper for description). Each systematic uncertainty sources 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 tau of highest-tau jet (see paper for description). Each systematic uncertainty sources 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 scalar sum of tau for all jets (see paper for description). Each systematic uncertainty sources 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 scalar sum of tau for all jets (see paper for description). Each systematic uncertainty sources 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 absolute rapidity of second leading jet. Each systematic uncertainty sources 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 absolute rapidity of second leading jet. Each systematic uncertainty sources 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 transverse momentum of third leading jet. Each systematic uncertainty sources 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 transverse momentum of third leading jet. Each systematic uncertainty sources 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 dijet invariant mass. Each systematic uncertainty sources 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 dijet invariant mass. Each systematic uncertainty sources 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 transverse momentum of the combined diphoton and dijet system. Each systematic uncertainty sources 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 transverse momentum of the combined diphoton and dijet system. Each systematic uncertainty sources 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 cosine of the decay angle in the Collins-Soper frame in bins of diphoton transverse momentum. Each systematic uncertainty sources 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 cosine of the decay angle in the Collins-Soper frame in bins of diphoton transverse momentum. Each systematic uncertainty sources 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 diphoton transverse momentum in jet multiplicity bins. Each systematic uncertainty sources 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 diphoton transverse momentum in jet multiplicity bins. Each systematic uncertainty sources 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 leading jet transverse momentum for exclusive one-jet events. Each systematic uncertainty sources 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 leading jet transverse momentum for exclusive one-jet events. Each systematic uncertainty sources 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.

Diphoton kinematic acceptances in percent for gluon fusion for each fiducial region/variable bin studied in this paper, defined as the probability to fulfil the diphoton kinematic criteria: pT(2gam) < 0.35 (0.25) for the leading (subleading) photon and |eta(gam)|<2.37. The factors are evaluated using the POWHEG event generator with MPI modelling and hadronisation turned off. Consistent results for the diphoton variables are obtained by HRes 2.2. Uncertainties are taken from PDF variations. QCD scale varaitions have a negligible impact on these factors.

Diphoton kinematic acceptances in percent for gluon fusion for each fiducial region/variable bin studied in this paper, defined as the probability to fulfil the diphoton kinematic criteria: pT(2gam) < 0.35 (0.25) for the leading (subleading) photon and |eta(gam)|<2.37. The factors are evaluated using the POWHEG event generator with MPI modelling and hadronisation turned off. Consistent results for the diphoton variables are obtained by HRes 2.2. Uncertainties are taken from PDF variations. QCD scale varaitions have a negligible impact on these factors.

Isolation efficiencies in percent for gluon fusion H -> 2gam for each fiducial region/variable bin measured in this analysis. The isolation efficiency is defined as the probability for both photons to fulfil the isolation criteria (ETiso < 14 GeV as described in the text) for events that pass the diphoton kinematic criteria. Uncertainties are assigned in the same way as for the non-perturbative correction factors: by varying the fragmentation and underlying event modelling. These factors can be multiplied by the kinematic acceptance factors (see table~ ef{tab:fid_acceptance}) to extrapolate an inclusive gluon fusion Higgs prediction to the fiducial volume used in this analysis.

Isolation efficiencies in percent for gluon fusion H -> 2gam for each fiducial region/variable bin measured in this analysis. The isolation efficiency is defined as the probability for both photons to fulfil the isolation criteria (ETiso < 14 GeV as described in the text) for events that pass the diphoton kinematic criteria. Uncertainties are assigned in the same way as for the non-perturbative correction factors: by varying the fragmentation and underlying event modelling. These factors can be multiplied by the kinematic acceptance factors (see table~ ef{tab:fid_acceptance}) to extrapolate an inclusive gluon fusion Higgs prediction to the fiducial volume used in this analysis.

Non-perturbative correction factors in percent accounting for the impact of hadronisation and the underlying event activity for all measured variables and fiducial regions. Uncertainties are evaluated by deriving these factors using different generators and tunes as described in the text.

Non-perturbative correction factors in percent accounting for the impact of hadronisation and the underlying event activity for all measured variables and fiducial regions. Uncertainties are evaluated by deriving these factors using different generators and tunes as described in the text.

Fiducial cross sections in fb from WH, ZH and ttH combined, in each variable bin and fiducial region.

Fiducial cross sections in fb from WH, ZH and ttH combined, in each variable bin and fiducial region.

Statistical bin-to-bin correlations between the 24 bins used in the analysis described in Phys.Lett. B753 (2016) 69-85 (arXiv:1508.02507). See Figure 3 of this paper for the bins used.

Trigger efficiency for simulated signal events as a function of the LLP decay position in the x&ndash;y plane (L_xy) for LLPs decaying in the barrel (|&eta;|&lt;1.4) for one of the low-E_T signal samples for HLT CalRatio triggers seeded by the high-E_T L1 triggers with E_T thresholds of 60 GeV and 100 GeV and by the two versions of the low-E_T L1 triggers. Only statistical uncertainties are shown.

Trigger efficiency for simulated signal events as a function of the LLP decay position in the x&ndash;y plane (L_xy) for LLPs decaying in the barrel (|&eta;|&lt;1.4) for one of the high-E_T signal samples for HLT CalRatio triggers seeded by the high-E_T L1 triggers with E_T thresholds of 60 GeV and 100 GeV and by the two versions of the low-E_T L1 triggers. Only statistical uncertainties are shown.

The NN output scores in the dijet control region for the low-E_T training with no adversary network. Statistical uncertainties are shown in all plots. In cases where training with adversary networks is considered, the systematic uncertainty related to modelling discrepancies is included as well.

The NN output scores in the dijet control region for the low-E_T training with an adversary network included. Statistical uncertainties are shown in all plots. In cases where training with adversary networks is considered, the systematic uncertainty related to modelling discrepancies is included as well.

The NN output scores in the dijet control region for the high-E_T training with no adversary network. Statistical uncertainties are shown in all plots. In cases where training with adversary networks is considered, the systematic uncertainty related to modelling discrepancies is included as well.

The NN output scores in the dijet control region for the high-E_T training with an adversary network included. Statistical uncertainties are shown in all plots. In cases where training with adversary networks is considered, the systematic uncertainty related to modelling discrepancies is included as well.

Distribution of the low-E_T per-event BDT in main data, BIB data and some of the benchmark signal samples after preselection. Only statistical uncertainties are shown.

Distribution of the high-E_T per-event BDT outputs in main data, BIB data and some of the benchmark signal samples after preselection. Only statistical uncertainties are shown.

Sequential impact of each requirement on the number of events passing the selection for the high-E_T selections. The signal columns represent the cumulative fraction of events passing the selection than the number of events.

Sequential impact of each requirement on the number of events passing the selection for the low-E_T selections. The signal columns represent the cumulative fraction of events passing the selection than the number of events.

Application of the modified ABCD method to the final high-E_T selections. The a priori estimate refers to the "pre-unblinding" case, where the data in region A are ignored by removing the Poisson constraint in that region and the signal strength is fixed to zero. This matches the simple N^bkg_A=(N^bkg_B&middot; N^bkg_C)/N^bkg_D relation. The a posteriori estimate refers to the "post-unblinding" case, including the observed data in region A in the background-only global fit, obtained by fixing the signal strength to 0 (background-only fit) or allowing it to float (signal-plus-background fit). The table also shows one set of representative signal yields in each selection for the signal-plus-background fit. Only statistical uncertainties are included in the quoted error of the background, while the uncertainties in the signal include those from both statistical and experimental sources.

Application of the modified ABCD method to the final low-E_T selections. The a priori estimate refers to the "pre-unblinding" case, where the data in region A are ignored by removing the Poisson constraint in that region and the signal strength is fixed to zero. This matches the simple N^bkg_A=(N^bkg_B&middot; N^bkg_C)/N^bkg_D relation. The a posteriori estimate refers to the "post-unblinding" case, including the observed data in region A in the background-only global fit, obtained by fixing the signal strength to 0 (background-only fit) or allowing it to float (signal-plus-background fit). The table also shows one set of representative signal yields in each selection for the signal-plus-background fit. Only statistical uncertainties are included in the quoted error of the background, while the uncertainties in the signal include those from both statistical and experimental sources.

95% CL expected and observed limits on the BR of SM Higgs bosons to pairs of neutral LLPs (B_{H&rarr; ss}), showing the &plusmn; 1 &sigma; (green) and &plusmn; 2 &sigma; (yellow) expected limit bands, as well as a comparison with the results from previous ATLAS searches [36,78]. The cross-section for SM Higgs boson gluon--gluon fusion production is assumed to be 48.6 pb.

Trigger efficiency of simulated signal events as a function of the LLP decay position in the z direction for LLPs decaying in the calorimeter endcaps (1.4 &le; |&eta;| &lt; 2.5) for one of the low-E_T signal samples for HLT CalRatio triggers seeded by the 60 GeV-high-E_T trigger and by the two versions of the low-E_T triggers.

Trigger efficiency of simulated signal events as a function of the LLP decay position in the z direction for LLPs decaying in the calorimeter endcaps (1.4 &le; |&eta;| &lt; 2.5) for one of the high-E_T signal samples for HLT CalRatio triggers seeded by the 60 GeV-high-E_T trigger and by the two versions of the low-E_T triggers.

The simulated efficiencies as a function of c times the mean proper lifetime (c&tau;) of s for several different MC samples. A weight-based extrapolation procedure is used to determine the efficiency at a given mean proper lifetime.

The simulated efficiencies as a function of c times the mean proper lifetime (c&tau;) of s for several different MC samples. A weight-based extrapolation procedure is used to determine the efficiency at a given mean proper lifetime.

The simulated efficiencies as a function of c times the mean proper lifetime (c&tau;) of s for several different MC samples. A weight-based extrapolation procedure is used to determine the efficiency at a given mean proper lifetime.

The simulated efficiencies as a function of c times the mean proper lifetime (c&tau;) of s for several different MC samples. A weight-based extrapolation procedure is used to determine the efficiency at a given mean proper lifetime.

The simulated efficiencies as a function of c times the mean proper lifetime (c&tau;) of s for several different MC samples. A weight-based extrapolation procedure is used to determine the efficiency at a given mean proper lifetime.

The simulated efficiencies as a function of c times the mean proper lifetime (c&tau;) of s for several different MC samples. A weight-based extrapolation procedure is used to determine the efficiency at a given mean proper lifetime.

The simulated efficiencies as a function of c times the mean proper lifetime (c&tau;) of s for several different MC samples. A weight-based extrapolation procedure is used to determine the efficiency at a given mean proper lifetime.

The simulated efficiencies as a function of c times the mean proper lifetime (c&tau;) of s for several different MC samples. A weight-based extrapolation procedure is used to determine the efficiency at a given mean proper lifetime.

The simulated efficiencies as a function of c times the mean proper lifetime (c&tau;) of s for several different MC samples. A weight-based extrapolation procedure is used to determine the efficiency at a given mean proper lifetime.

The simulated efficiencies as a function of c times the mean proper lifetime (c&tau;) of s for several different MC samples. A weight-based extrapolation procedure is used to determine the efficiency at a given mean proper lifetime.

The simulated efficiencies as a function of c times the mean proper lifetime (c&tau;) of s for several different MC samples. A weight-based extrapolation procedure is used to determine the efficiency at a given mean proper lifetime.

The simulated efficiencies as a function of c times the mean proper lifetime (c&tau;) of s for several different MC samples. A weight-based extrapolation procedure is used to determine the efficiency at a given mean proper lifetime.

The simulated efficiencies as a function of c times the mean proper lifetime (c&tau;) of s for several different MC samples. A weight-based extrapolation procedure is used to determine the efficiency at a given mean proper lifetime.

The simulated efficiencies as a function of c times the mean proper lifetime (c&tau;) of s for several different MC samples. A weight-based extrapolation procedure is used to determine the efficiency at a given mean proper lifetime.

The event BDT in the dijet control region for the low-E_T training training. The uncertainties are combined statistical and ML modelling systematic uncertainty.

The event BDT in the dijet control region for the high-E_T training. The uncertainties are combined statistical and ML modelling systematic uncertainty.

The 95% CL observed limits, expected limits and &plusmn; 1 &sigma; and 2 &sigma; bands for the &Phi; mass of 60 GeV compared to the results from the 2016-data analysis and subsequent combinations, where available.

The 95% CL observed limits, expected limits and &plusmn; 1 &sigma; and 2 &sigma; bands for the &Phi; mass of 60 GeV compared to the results from the 2016-data analysis and subsequent combinations, where available.

The 95% CL observed limits, expected limits and &plusmn; 1 &sigma; and 2 &sigma; bands for the &Phi; mass 125 GeV, compared to the results from the 2016-data analysis and subsequent combinations, where available.

The 95% CL observed limits, expected limits and &plusmn; 1 &sigma; and 2 &sigma; bands for the &Phi; mass 125 GeV, compared to the results from the 2016-data analysis and subsequent combinations, where available. The 125 GeV mediator is assumed to be the SM Higgs boson.

The 95% CL observed limits, expected limits and &plusmn; 1 &sigma; and 2 &sigma; bands for the &Phi; mass 125 GeV, compared to the results from the 2016-data analysis and subsequent combinations, where available. The 125 GeV mediator is assumed to be the SM Higgs boson.

The 95% CL observed limits, expected limits and &plusmn; 1 &sigma; and 2 &sigma; bands for the &Phi; mass of 200 GeV, compared to the results from the 2016-data analysis and subsequent combinations, where available.

The 95% CL observed limits, expected limits and &plusmn; 1 &sigma; and 2 &sigma; bands for the &Phi; mass of 400 GeV, compared to the results from the 2016-data analysis and subsequent combinations, where available.

The 95% CL observed limits, expected limits and &plusmn; 1 &sigma; and 2 &sigma; bands for the &Phi; mass 600 GeV, compared to the results from the 2016-data analysis and subsequent combinations, where available.

The 95% CL observed limits, expected limits and &plusmn; 1 &sigma; and 2 &sigma; bands for the &Phi; mass of 600 GeV, compared to the results from the 2016-data analysis and subsequent combinations, where available.

The 95% CL observed limits, expected limits and &plusmn; 1 &sigma; and 2 &sigma; bands for the &Phi; masses of of 1000 GeV, compared to the results from the 2016-data analysis and subsequent combinations, where available.

The 95% CL observed limits, expected limits and &plusmn; 1 &sigma; and 2 &sigma; bands for the &Phi; masses of of 1000 GeV, compared to the results from the 2016-data analysis and subsequent combinations, where available.

The 95% CL observed limits, expected limits and &plusmn; 1 &sigma; and 2 &sigma; bands for the &Phi; masses of of 1000 GeV, compared to the results from the 2016-data analysis and subsequent combinations, where available.

The 95% CL observed limits, expected limits and &plusmn; 1 &sigma; and 2 &sigma; bands for the &Phi; masses of of 1000 GeV, compared to the results from the 2016-data analysis and subsequent combinations, where available.

Efficiency for an event to enter Region A of the high-E_T selection, as a function of the two LLP kinematics, decay type and decay position. LLP p_T is binned in the ranges of [0, 50 , 100, 200 , 400, 1600] GeV (5 bins), the LLP decay position is binned in decay position in L_xy in [0, 1.5, 2, 2.5, 3, 3.5, 3.9, &infin;] m for LLPs with |&eta;| &lt; 1.5 and L_z in [0, 3.6, 4.2, 4.8, 5.5, 6, &infin; ] m for LLPs with |&eta;|geq1.5, 13 bins in all. Finally, four decay types are considered: LLPs decaying to pairs of c, b, t, or &tau; in bins 0, 1, 2, 3 respectively. The efficiency is presented as a function of "Bin Index", which is calculated as follows: Bin Index = (decay position bin index ) &times; (number of p_T bins &times; number of decay type bins) + p_T bin index * (number of decay type bin) + decay type bin index. The efficiency for a given pair-produced LLP sample can be obtained by summing the efficiency values for each event as extracted from this map, and dividing it by the total number of events in the sample. The efficiency map is symmetric between the LLPs, so the choice of LLP1 and LLP2 is arbitrary. For the high-E_T selections, for overall efficiencies above 0.5%, the results are typically accurate to around 25%, but below this the efficiency can be overestimated and therefore should not be used for re-interpration.

Efficiency for an event to enter Region A of the low-E_T selection, as a function of the two LLP kinematics, decay type and decay position. LLP p_T is binned in the ranges of [0, 50 , 100, 200 , 400, 1600] GeV (5 bins), the LLP decay position is binned in L_xy in [0, 1.5, 2, 2.5, 3, 3.5, 3.9, &infin;] m for LLPs with |&eta;| &lt; 1.5 and L_z in [0, 3.6, 4.2, 4.8, 5.5, 6, &infin; ] m for LLPs with |&eta;|geq1.5, 13 bins in all. Finally, four decay types are considered: LLPs decaying to pairs of c, b, t, or &tau; in bins 0, 1, 2, 3 respectively. The efficiency is presented as a function of "Bin Index", which is calculated as follows: Bin Index = (decay position bin index ) &times; (number of p_T bins &times; number of decay type bins) + p_T bin index * (number of decay type bin) + decay type bin index. The efficiency for a given pair-produced LLP sample can be obtained by summing the efficiency values for each event as extracted from this map, and dividing it by the total number of events in the sample. The efficiency map is symmetric between the LLPs, so the choice of LLP1 and LLP2 is arbitrary. For the low-E_T selections, for overall efficiencies above 0.15%, the results are typically accurate to around 33%, and below this the efficiency is typically accurate up to a factor of 3.