Difference: PhysicsResultsSUS16033-PAPER (1 vs. 34)

Revision 342019-08-08 - TribeniMishra1

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META TOPICPARENT name="PhysicsResultsSUS"

Search for supersymmetry in multijet events with missing transverse momentum in proton-proton collisions at 13 TeV (SUS-16-033)

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  • AnalysisBins_BTag0_RzGamma_Run2_signal_ZJets_supplementary.pdf: Distribution of $R_{{\rm Z}/\gamma}$ with baseline selection applied in the 46 search bins with $N_{\rm b-jet}=0$. Because of limited statistical precision in the simulated event samples at large $N_{\rm jet}$, the transfer factors determined for the $8\leq$N_{\rm jet}$\leq 9$ region are also used for the $N_{\rm jet}10$ region. Points with error bars show the computed value in each bin with statistical uncertainties.

  • Distribution of $R_{{\rm Z}/\gamma}$ with baseline selection applied in the 46 search bins with $N_{\rm b-jet}=0$. Because of limited statistical precision in the simulated event samples at large $N_{\rm jet}$, the transfer factors determined for the $8\leq$N_{\rm jet}$\leq 9$ region are also used for the $N_{\rm jet}10$ region. Points with error bars show the computed value in each bin with statistical uncertainties.:
    AnalysisBins_BTag0_RzGamma_Run2_signal_ZJets_supplementary.png
 
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Revision 332018-03-06 - WolfgangAdam

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META TOPICPARENT name="PhysicsResultsSUS"

Search for supersymmetry in multijet events with missing transverse momentum in proton-proton collisions at 13 TeV (SUS-16-033)

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ExpVsPre_MHT_baseline_Plot.png Figure 2b : The lost-lepton background as a function of $H_{\rm T}^{\rm miss}$ as determined directly from ttbar, single top quark, W+jets, diboson, and rare-event simulation (points, with statistical uncertainties) and as predicted by applying the lost-lepton background determination procedure to simulated electron and muon control samples (histograms, with statistical uncertainties). The results in the lower panel are obtained through bin-by-bin division of the results in the upper panel, including the uncertainties, by the central values of the "predicted" results.
ExpVsPre_NJets_baseline_Plot.png Figure 2c : The lost-lepton background as a function of the number of jets as determined directly from ttbar, single top quark, W+jets, diboson, and rare-event simulation (points, with statistical uncertainties) and as predicted by applying the lost-lepton background determination procedure to simulated electron and muon control samples (histograms, with statistical uncertainties). The results in the lower panel are obtained through bin-by-bin division of the results in the upper panel, including the uncertainties, by the central values of the "predicted" results.
ExpVsPre_NBtag_baseline_Plot.png Figure 2d: The lost-lepton background as a function of the number of b-tagged jets as determined directly from ttbar, single top quark, W+jets, diboson, and rare-event simulation (points, with statistical uncertainties) and as predicted by applying the lost-lepton background determination procedure to simulated electron and muon control samples (histograms, with statistical uncertainties). The results in the lower panel are obtained through bin-by-bin division of the results in the upper panel, including the uncertainties, by the central values of the "predicted" results.
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ExpVsCS_HT_baseline_Plot.png Figure 3a : Comparison of the number of expected lost-lepton background events in the zero (selected) lepton search region (points, with statistical uncertainties) and the sum of single electron and muon control sample events (histograms, with statistical uncertainties) as a function of $H_{\rm T}$. The simulation includes ttbar, single top quark, W+jets, diboson, and rare-event simulation.
ExpVsCS_MHT_baseline_Plot.png Figure 3b : Comparison of the number of expected lost-lepton background events in the zero (selected) lepton search region (points, with statistical uncertainties) and the sum of single electron and muon control sample events (histograms, with statistical uncertainties) as a function of $H_{\rm T}^{\rm miss}$. The simulation includes ttbar, single top quark, W+jets, diboson, and rare-event simulation.
ExpVsCS_NJets_baseline_Plot.png Figure 3c : Comparison of the number of expected lost-lepton background events in the zero (selected) lepton search region (points, with statistical uncertainties) and the sum of single electron and muon control sample events (histograms, with statistical uncertainties) as a function of the number of jets. The simulation includes ttbar, single top quark, W+jets, diboson, and rare-event simulation.
ExpVsCS_NBtag_baseline_Plot.png Figure 3d : Comparison of the number of expected lost-lepton background events in the zero (selected) lepton search region (points, with statistical uncertainties) and the sum of single electron and muon control sample events (histograms, with statistical uncertainties) as a function of the number of b-tagged jets. The simulation includes ttbar, single top quark, W+jets, diboson, and rare-event simulation.
ExpVsCS_search_baseline_Plot.png Figure 4 : Comparison of the number of expected lost-lepton background events in the zero (selected) lepton search region (points, with statistical uncertainties) and the sum of single electron and muon control sample events (histograms, with statistical uncertainties) as a function of the search region bin number of the analysis. The simulation includes ttbar, single top quark, W+jets, diboson, and rare-event simulation.
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ExpVsCS_HT_baseline_Plot.png Figure 3a : Comparison of the number of expected lost-lepton background events in the zero (selected) lepton search region (histogram, with statistical uncertainties) and the sum of single electron and muon control sample events (points, with statistical uncertainties) as a function of $H_{\rm T}$. The simulation includes ttbar, single top quark, W+jets, diboson, and rare-event simulation.
ExpVsCS_MHT_baseline_Plot.png Figure 3b : Comparison of the number of expected lost-lepton background events in the zero (selected) lepton search region (histogram, with statistical uncertainties) and the sum of single electron and muon control sample events (points, with statistical uncertainties) as a function of $H_{\rm T}^{\rm miss}$. The simulation includes ttbar, single top quark, W+jets, diboson, and rare-event simulation.
ExpVsCS_NJets_baseline_Plot.png Figure 3c : Comparison of the number of expected lost-lepton background events in the zero (selected) lepton search region (histogram, with statistical uncertainties) and the sum of single electron and muon control sample events (points, with statistical uncertainties) as a function of the number of jets. The simulation includes ttbar, single top quark, W+jets, diboson, and rare-event simulation.
ExpVsCS_NBtag_baseline_Plot.png Figure 3d : Comparison of the number of expected lost-lepton background events in the zero (selected) lepton search region (histogram, with statistical uncertainties) and the sum of single electron and muon control sample events (points, with statistical uncertainties) as a function of the number of b-tagged jets. The simulation includes ttbar, single top quark, W+jets, diboson, and rare-event simulation.
ExpVsCS_search_baseline_Plot.png Figure 4 : Comparison of the number of expected lost-lepton background events in the zero (selected) lepton search region (histogram, with statistical uncertainties) and the sum of single electron and muon control sample events (points, with statistical uncertainties) as a function of the search region bin number of the analysis. The simulation includes ttbar, single top quark, W+jets, diboson, and rare-event simulation.
 
Plot_WgunTemplate.png Figure 5 : The hadronically-decaying $\tau$ lepton ($\tau_{\rm h}$) response templates: distributions of the ratio of $\tau_{\rm h}$ visible-$p_{\rm T}$ to true-$p_{\rm T}$, $p_{\rm T}(\tau_{\rm h}^{\rm visible})/p_{\rm T}(\tau_{\rm h}^{\rm gen})$, in intervals of $p_{\rm T}(\tau_{\rm h}^{\rm gen})$ as determined from a simulation of single ${\rm W}\rightarrow\tau_{\rm h}\nu_{\tau}$ decay events.
PClosure_HT_delphi_stacked_ARElog116_ARElog115_Plot_kRed-9.png Figure 6a : Distributions of $H_{\rm T}$ in background events with a hadronically decaying $\tau$ lepton as predicted directly from simulation (points, with statistical uncertainties) and as predicted by applying the hadronically decaying $\tau$ lepton background determination procedure to simulated muon control sample (shaded regions), for the baseline selection. The simulation includes ttbar, W+jets, and single top quark process events.
PClosure_MHT_delphi_stacked_ARElog116_ARElog115_Plot_kRed-9.png Figure 6b : Distributions of $H_{\rm T}^{\rm miss}$ in background events with a hadronically decaying $\tau$ lepton as predicted directly from simulation (points, with statistical uncertainties) and as predicted by applying the hadronically decaying $\tau$ lepton background determination procedure to simulated muon control sample (shaded regions), for the baseline selection. The simulation includes ttbar, W+jets, and single top quark process events.

Revision 322018-03-06 - SimonThomasKurz

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Search for supersymmetry in multijet events with missing transverse momentum in proton-proton collisions at 13 TeV (SUS-16-033)

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Revision 312017-09-19 - LesyaShchutska

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Search for supersymmetry in multijet events with missing transverse momentum in proton-proton collisions at 13 TeV (SUS-16-033)

Revision 302017-08-30 - KevinPedro

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META TOPICPARENT name="RA2b13TeV"

Search for supersymmetry in multijet events with missing transverse momentum in proton-proton collisions at 13 TeV (SUS-16-033)

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SUS13012_SUS16033kevin_surv_100_mg_rebin_VS_mz1_rebin2_sp.pdf Figure 27a : Survival probability, defined as the fraction of model points that are not excluded at 95% CL as computed using the CLs criterion, in the m(${\tilde{\rm g}}$)-m($\chi_{1}^{0}$) plane, for the signal model points in a pMSSM-19 scan [1]. For small $\chi_1^0$ mass, the range of excluded gluino mass exceeds typical SMS limits; this is mostly due to the presence of relatively light squarks in pMSSM model points with large gluino mass, which are not present in simplified models. White space indicates where the density of scan points is 0.
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SUS13012_SUS16033kevin_surv_100_mg_rebin_VS_mz1_rebin2_sp.png Figure 27a : Survival probability, defined as the fraction of model points that are not excluded at 95% CL as computed using the CLs criterion, in the $m_{\tilde{\rm g}}-m_{\tilde{\chi}_1^0}$ plane, for the signal model points in a pMSSM-19 scan [1]. For small $\tilde{\chi}_1^0$ mass, the range of excluded gluino mass exceeds typical SMS limits; this is mostly due to the presence of relatively light squarks in pMSSM model points with large gluino mass, which are not present in simplified models. White space indicates where the density of scan points is 0.
 
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SUS13012_SUS16033kevin_surv_100_mLCSP_rebin_VS_mz1_rebin2_sp.pdf Figure 27b : Survival probability, defined as the fraction of model points that are not excluded at 95% CL as computed using the CLs criterion, in the m(LCSP)-m($\chi_{1}^{0}$) plane, for the signal model points in a pMSSM-19 scan [1]. LCSP denotes the lightest colored SUSY particle. White space indicates where the density of scan points is 0.
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SUS13012_SUS16033kevin_surv_100_mLCSP_rebin_VS_mz1_rebin2_sp.png Figure 27b : Survival probability, defined as the fraction of model points that are not excluded at 95% CL as computed using the CLs criterion, in the $m_{\rm LCSP}-m_{\tilde{\chi}_1^0}$ plane, for the signal model points in a pMSSM-19 scan [1]. LCSP denotes the lightest colored SUSY particle. White space indicates where the density of scan points is 0.
 
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SUS13012_SUS16033kevin_surv_100_mg_rebin_VS_mz1_rebin2.pdf Figure 28a : Posterior density, computed using the methodology described in [1], in the m($\tilde{g}$)-m($\chi_{1}^{0}$) plane of the pMSSM-19. The "counts-based" construction is used for computation of the likelihood. The peak in the posterior density at low m($\chi_{1}^{0}$) is due to the requirement that all four neutralino masses be less than 3 TeV in the parameter scan.
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SUS13012_SUS16033kevin_surv_100_mg_rebin_VS_mz1_rebin2.png Figure 28a : Posterior density, computed using the methodology described in [1], in the $m_{\tilde{\rm g}}-m_{\tilde{\chi}_1^0}$ plane of the pMSSM-19. The "counts-based" construction is used for computation of the likelihood. The peak in the posterior density at low $m_{\tilde{\chi}_1^0}$ is due to the requirement that all four neutralino masses be less than 3 TeV in the parameter scan.
 
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SUS13012_SUS16033kevin_surv_100_mLCSP_rebin_VS_mz1_rebin2.pdf Figure 28b : Posterior density, computed using the methodology described in [1], in the m(LCSP)-m($\chi_{1}^{0}$) plane of the pMSSM-19, where LCSP denotes the lightest colored SUSY particle. The "counts-based" construction is used for the computation of the likelhood.
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SUS13012_SUS16033kevin_surv_100_mLCSP_rebin_VS_mz1_rebin2.png Figure 28b : Posterior density, computed using the methodology described in [1], in the $m_{\rm LCSP}-m_{\tilde{\chi}_1^0}$ plane of the pMSSM-19, where LCSP denotes the lightest colored SUSY particle. The "counts-based" construction is used for the computation of the likelhood.

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References

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[1] CMS Collaboration, “Phenomenological MSSM interpretation of CMS searches in pp collisions at sqrt(s) = 7 and 8 TeV”, JHEP 10 (2016) 129, doi:10.1007/JHEP10(2016)129, arXiv:1606.03577.

 
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Revision 292017-08-26 - SamBein

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META TOPICPARENT name="RA2b13TeV"

Search for supersymmetry in multijet events with missing transverse momentum in proton-proton collisions at 13 TeV (SUS-16-033)

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Revision 282017-08-26 - SamBein

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META TOPICPARENT name="RA2b13TeV"

Search for supersymmetry in multijet events with missing transverse momentum in proton-proton collisions at 13 TeV (SUS-16-033)

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Figure Caption
t1-signal-q-plot-174-bins.png Figure 18a : The sensitivity of the analysis to different direct gluino production signal models as a function of the analysis binning. The upper panel shows the total predicted SM backgrounds and the expected number of signal events in 35.9 ${\rm fb}^{-1}$ of data for six representative model points per analysis bin. The bottom panel shows the expected sensitivity, expressed in terms of the figure of merit Q, per analysis bin.
t2-signal-q-plot-174-bins.png Figure 18b : The sensitivity of the analysis to different direct squark production signal models as a function of the analysis binning. The upper panel shows the total predicted SM backgrounds and the expected number of signal events in 35.9 ${\rm fb}^{-1}$ of data for six representative model points per analysis bin. The bottom panel shows the expected sensitivity, expressed in terms of the figure of merit Q, per analysis bin.

Figure Caption
njets-projection.png Figure 19a : One-dimensional projection of observed number of events and pre-fit background predictions in the search region in $N_{\rm jet}$.
njets-projection-pull.png Figure 19b : The same distributions shown in Add. Fig. 19a, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
nbjets-projection.png Figure 19c : One-dimensional projection of observed number of events and pre-fit background predictions in the search region in $N_{\rm b-jet}$.
nbjets-projection-pull.png Figure 19d : The same distributions shown in Add. Fig. 19c, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
mht-projection.png Figure 19e : One-dimensional projection of observed number of events and pre-fit background predictions in the search region in $H_{\rm T}^{\rm miss}$.
mht-projection-pull.png Figure 19f : The same distributions shown in Add. Fig. 19e, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.

Figure Caption
T1tttt-projection-pull.png Figure 20a : The same distributions shown in Fig. 11a in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
T1bbbb-projection-pull.png Figure 20b : The same distributions shown in Fig. 11b in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
T1qqqq-projection-pull.png Figure 20c : The same distributions shown in Fig. 11c in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
T2tt-projection-pull.png Figure 20d : The same distributions shown in Fig. 11d in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
T2bb-projection-pull.png Figure 20e : The same distributions shown in Fig. 11e in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
T2qq-projection-pull.png Figure 20f : The same distributions shown in Fig. 11f in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.

Figure Caption
2D-T1tttt.png Figure 21a : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\rm jet}$ and $N_{\rm b-jet}$, integrated over search regions with $H_{\rm T}^{\rm miss}&amp;gt;750$ GeV and $H_{\rm T}&amp;gt;750$ GeV. An example T1tttt signal scenario with $m_{\tilde{\rm g}}=1500$ GeV and $m_{\tilde{\chi}_1^0}=100$ GeV is shown by the (stacked) purple histogram.
2D-T1tttt-pull.png Figure 21b : The same distributions shown in Add. Fig. 21a, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
2D-T1bbbb.png Figure 21c : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\rm jet}$ and $N_{\rm b-jet}$, integrated over search regions with $H_{\rm T}^{\rm miss}&amp;gt;750$ GeV and $H_{\rm T}&amp;gt;750$ GeV. An example T1bbbb signal scenario with $m_{\tilde{\rm g}}=1500$ GeV and $m_{\tilde{\chi}_1^0}=100$ GeV is shown by the (stacked) purple histogram.
2D-T1bbbb-pull.png Figure 21d : The same distributions shown in Add. Fig. 21c, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
2D-T1qqqq.png Figure 21e : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\rm jet}$ and $N_{\rm b-jet}$, integrated over search regions with $H_{\rm T}^{\rm miss}&amp;gt;750$ GeV and $H_{\rm T}&amp;gt;750$ GeV. An example T1qqqq signal scenario with $m_{\tilde{\rm g}}=1400$ GeV and $m_{\tilde{\chi}_1^0}=100$ GeV is shown by the (stacked) purple histogram.
2D-T1qqqq-pull.png Figure 21f : The same distributions shown in Add. Fig. 21e, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
2D-T2tt.png Figure 21g : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\rm jet}$ and $N_{\rm b-jet}$, integrated over search regions with $H_{\rm T}^{\rm miss}&amp;gt;750$ GeV and $H_{\rm T}&amp;gt;750$ GeV. An example T2tt signal scenario with $m_{\tilde{\rm t}}=700$ GeV and $m_{\tilde{\chi}_1^0}=50$ GeV is shown by the (stacked) purple histogram.
2D-T2tt-pull.png Figure 21h : The same distributions shown in Add. Fig. 21g, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
2D-T2bb.png Figure 21i : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\rm jet}$ and $N_{\rm b-jet}$, integrated over search regions with $H_{\rm T}^{\rm miss}&amp;gt;750$ GeV and $H_{\rm T}&amp;gt;750$ GeV. An example T2bb signal scenario with $m_{\tilde{\rm b}}=650$ GeV and $m_{\tilde{\chi}_1^0}=1$ GeV is shown by the (stacked) purple histogram.
2D-T2bb-pull.png Figure 21j : The same distributions shown in Add. Fig. 21i, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
2D-T2qq.png Figure 21k : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\rm jet}$ and $N_{\rm b-jet}$, integrated over search regions with $H_{\rm T}^{\rm miss}&amp;gt;750$ GeV and $H_{\rm T}&amp;gt;750$ GeV. An example T2qq signal scenario with $m_{\tilde{\rm b}}=1000$ GeV and $m_{\tilde{\chi}_1^0}=100$ GeV is shown by the (stacked) purple histogram.
2D-T2qq-pull.png Figure 21l : The same distributions shown in Add. Fig. 21k, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.

Figure Caption
results-plot-prefit-35_9_pre_app-log-pull.png Figure 22 : The same distributions shown in Fig. 9 in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.

Figure Caption
results-plot-prefit-12-asrs-35_9-log-pull.png Figure 23 : The same distributions shown in Fig. 10 in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.

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Results: yields vs. background prediction, select kinematic distributions

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SUS13012_SUS16033kevin_surv_100_mg_rebin_VS_mz1_rebin2_sp.pdf Figure 27a : Survival probability, defined as the fraction of model points that are not excluded at 95% CL as computed using the CLs criterion, in the m(${\tilde{\rm g}}$)-m($\chi_{1}^{0}$) plane, for the signal model points in a pMSSM-19 scan [1]. For small $\chi_1^0$ mass, the range of excluded gluino mass exceeds typical SMS limits; this is mostly due to the presence of relatively light squarks in pMSSM model points with large gluino mass, which are not present in simplified models. White space indicates where the density of scan points is 0.
Figure Caption
SUS13012_SUS16033kevin_surv_100_mLCSP_rebin_VS_mz1_rebin2_sp.pdf Figure 27b : Survival probability, defined as the fraction of model points that are not excluded at 95% CL as computed using the CLs criterion, in the m(LCSP)-m($\chi_{1}^{0}$) plane, for the signal model points in a pMSSM-19 scan [1]. LCSP denotes the lightest colored SUSY particle. White space indicates where the density of scan points is 0.

Figure Caption
SUS13012_SUS16033kevin_surv_100_mg_rebin_VS_mz1_rebin2.pdf Figure 28a : Posterior density, computed using the methodology described in [1], in the m($\tilde{g}$)-m($\chi_{1}^{0}$) plane of the pMSSM-19. The "counts-based" construction is used for computation of the likelihood. The peak in the posterior density at low m($\chi_{1}^{0}$) is due to the requirement that all four neutralino masses be less than 3 TeV in the parameter scan.
Figure Caption
SUS13012_SUS16033kevin_surv_100_mLCSP_rebin_VS_mz1_rebin2.pdf Figure 28b : Posterior density, computed using the methodology described in [1], in the m(LCSP)-m($\chi_{1}^{0}$) plane of the pMSSM-19, where LCSP denotes the lightest colored SUSY particle. The "counts-based" construction is used for the computation of the likelhood.

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Revision 272017-08-18 - SamBein

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META TOPICPARENT name="RA2b13TeV"

Search for supersymmetry in multijet events with missing transverse momentum in proton-proton collisions at 13 TeV (SUS-16-033)

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Results: additional interpretation

 
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Figure Caption
t1-signal-q-plot-174-bins.png Figure 18a : The sensitivity of the analysis to different direct gluino production signal models as a function of the analysis binning. The upper panel shows the total predicted SM backgrounds and the expected number of signal events in 35.9 ${\rm fb}^{-1}$ of data for six representative model points per analysis bin. The bottom panel shows the expected sensitivity, expressed in terms of the figure of merit Q, per analysis bin.
t2-signal-q-plot-174-bins.png Figure 18b : The sensitivity of the analysis to different direct squark production signal models as a function of the analysis binning. The upper panel shows the total predicted SM backgrounds and the expected number of signal events in 35.9 ${\rm fb}^{-1}$ of data for six representative model points per analysis bin. The bottom panel shows the expected sensitivity, expressed in terms of the figure of merit Q, per analysis bin.

Figure Caption
njets-projection.png Figure 19a : One-dimensional projection of observed number of events and pre-fit background predictions in the search region in $N_{\rm jet}$.
njets-projection-pull.png Figure 19b : The same distributions shown in Add. Fig. 19a, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
nbjets-projection.png Figure 19c : One-dimensional projection of observed number of events and pre-fit background predictions in the search region in $N_{\rm b-jet}$.
nbjets-projection-pull.png Figure 19d : The same distributions shown in Add. Fig. 19c, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
mht-projection.png Figure 19e : One-dimensional projection of observed number of events and pre-fit background predictions in the search region in $H_{\rm T}^{\rm miss}$.
mht-projection-pull.png Figure 19f : The same distributions shown in Add. Fig. 19e, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.

Figure Caption
T1tttt-projection-pull.png Figure 20a : The same distributions shown in Fig. 11a in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
T1bbbb-projection-pull.png Figure 20b : The same distributions shown in Fig. 11b in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
T1qqqq-projection-pull.png Figure 20c : The same distributions shown in Fig. 11c in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
T2tt-projection-pull.png Figure 20d : The same distributions shown in Fig. 11d in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
T2bb-projection-pull.png Figure 20e : The same distributions shown in Fig. 11e in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
T2qq-projection-pull.png Figure 20f : The same distributions shown in Fig. 11f in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.

Figure Caption
2D-T1tttt.png Figure 21a : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\rm jet}$ and $N_{\rm b-jet}$, integrated over search regions with $H_{\rm T}^{\rm miss}&amp;gt;750$ GeV and $H_{\rm T}&amp;gt;750$ GeV. An example T1tttt signal scenario with $m_{\tilde{\rm g}}=1500$ GeV and $m_{\tilde{\chi}_1^0}=100$ GeV is shown by the (stacked) purple histogram.
2D-T1tttt-pull.png Figure 21b : The same distributions shown in Add. Fig. 21a, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
2D-T1bbbb.png Figure 21c : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\rm jet}$ and $N_{\rm b-jet}$, integrated over search regions with $H_{\rm T}^{\rm miss}&amp;gt;750$ GeV and $H_{\rm T}&amp;gt;750$ GeV. An example T1bbbb signal scenario with $m_{\tilde{\rm g}}=1500$ GeV and $m_{\tilde{\chi}_1^0}=100$ GeV is shown by the (stacked) purple histogram.
2D-T1bbbb-pull.png Figure 21d : The same distributions shown in Add. Fig. 21c, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
2D-T1qqqq.png Figure 21e : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\rm jet}$ and $N_{\rm b-jet}$, integrated over search regions with $H_{\rm T}^{\rm miss}&amp;gt;750$ GeV and $H_{\rm T}&amp;gt;750$ GeV. An example T1qqqq signal scenario with $m_{\tilde{\rm g}}=1400$ GeV and $m_{\tilde{\chi}_1^0}=100$ GeV is shown by the (stacked) purple histogram.
2D-T1qqqq-pull.png Figure 21f : The same distributions shown in Add. Fig. 21e, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
2D-T2tt.png Figure 21g : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\rm jet}$ and $N_{\rm b-jet}$, integrated over search regions with $H_{\rm T}^{\rm miss}&amp;gt;750$ GeV and $H_{\rm T}&amp;gt;750$ GeV. An example T2tt signal scenario with $m_{\tilde{\rm t}}=700$ GeV and $m_{\tilde{\chi}_1^0}=50$ GeV is shown by the (stacked) purple histogram.
2D-T2tt-pull.png Figure 21h : The same distributions shown in Add. Fig. 21g, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
2D-T2bb.png Figure 21i : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\rm jet}$ and $N_{\rm b-jet}$, integrated over search regions with $H_{\rm T}^{\rm miss}&amp;gt;750$ GeV and $H_{\rm T}&amp;gt;750$ GeV. An example T2bb signal scenario with $m_{\tilde{\rm b}}=650$ GeV and $m_{\tilde{\chi}_1^0}=1$ GeV is shown by the (stacked) purple histogram.
2D-T2bb-pull.png Figure 21j : The same distributions shown in Add. Fig. 21i, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
2D-T2qq.png Figure 21k : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\rm jet}$ and $N_{\rm b-jet}$, integrated over search regions with $H_{\rm T}^{\rm miss}&amp;gt;750$ GeV and $H_{\rm T}&amp;gt;750$ GeV. An example T2qq signal scenario with $m_{\tilde{\rm b}}=1000$ GeV and $m_{\tilde{\chi}_1^0}=100$ GeV is shown by the (stacked) purple histogram.
2D-T2qq-pull.png Figure 21l : The same distributions shown in Add. Fig. 21k, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
 
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Figure Caption
results-plot-prefit-35_9_pre_app-log-pull.png Figure 22 : The same distributions shown in Fig. 9 in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.

Figure Caption
results-plot-prefit-12-asrs-35_9-log-pull.png Figure 23 : The same distributions shown in Fig. 10 in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.

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Revision 262017-07-20 - KevinPedro

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META TOPICPARENT name="RA2b13TeV"

Search for supersymmetry in multijet events with missing transverse momentum in proton-proton collisions at 13 TeV (SUS-16-033)

Line: 92 to 92
 
Figure Caption
Changed:
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T1tttt-projection-pull.png Figure 20a : The same distributions shown in Fig. 11a in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
T1bbbb-projection-pull.png Figure 20b : The same distributions shown in Fig. 11b in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
T1qqqq-projection-pull.png Figure 20c : The same distributions shown in Fig. 11c in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
T2tt-projection-pull.png Figure 20d : The same distributions shown in Fig. 11d in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
T2bb-projection-pull.png Figure 20e : The same distributions shown in Fig. 11e in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
T2qq-projection-pull.png Figure 20f : The same distributions shown in Fig. 11f in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
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T1tttt-projection-pull.png Figure 20a : The same distributions shown in Fig. 11a in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
T1bbbb-projection-pull.png Figure 20b : The same distributions shown in Fig. 11b in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
T1qqqq-projection-pull.png Figure 20c : The same distributions shown in Fig. 11c in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
T2tt-projection-pull.png Figure 20d : The same distributions shown in Fig. 11d in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
T2bb-projection-pull.png Figure 20e : The same distributions shown in Fig. 11e in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
T2qq-projection-pull.png Figure 20f : The same distributions shown in Fig. 11f in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
 
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results-plot-prefit-35_9_pre_app-log-pulll.png Figure 22 : The same distributions shown in Fig. 9 in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
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results-plot-prefit-35_9_pre_app-log-pull.png Figure 22 : The same distributions shown in Fig. 9 in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
 
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Revision 252017-05-20 - JohnBradmillerFeld

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/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/rands-closure-ht.png Figure 7a : Distribution of $H_{\rm T}$ in background events with QCD multi-jet events predicted directly from simulation (points, with statistical uncertainties) and as predicted by applying the rebalance and smear background determination procedure to a simulated QCD sample (shaded regions), after a modified baseline event selection.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/rands-closure-mht.png Figure 7b : Distribution of $H_{\rm T}^{\rm miss}$ in background events with QCD multi-jet events predicted directly from simulation (points, with statistical uncertainties) and as predicted by applying the rebalance and smear background determination procedure to a simulated QCD sample (shaded regions), after a modified baseline event selection.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/rands-closure-njets.png Figure 7c : Distribution of the number of jets in background events with QCD multi-jet events predicted directly from simulation (points, with statistical uncertainties) and as predicted by applying the rebalance and smear background determination procedure to a simulated QCD sample (shaded regions), after a modified baseline event selection.
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/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/rands-closure-btags.png Figure 7d : Distribution of the number of b-tagged jetsin background events with QCD multi-jet events predicted directly from simulation (points, with statistical uncertainties) and as predicted by applying the rebalance and smear background determination procedure to a simulated QCD sample (shaded regions), after a modified baseline event selection.
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/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/rands-closure-btags.png Figure 7d : Distribution of the number of b-tagged jetsin background events with QCD multi-jet events predicted directly from simulation (points, with statistical uncertainties) and as predicted by applying the rebalance and smear background determination procedure to a simulated QCD sample (shaded regions), after a modified baseline event selection.
 
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/rands-closure-dphi1.png Figure 8a : Distribution of the azimuthal separation between the $H_{\rm T}^{\rm miss}$ and the first jet in background events with QCD multi-jet events predicted directly from simulation (points, with statistical uncertainties) and as predicted by applying the rebalance and smear background determination procedure to a simulated QCD sample (shaded regions), after a modified baseline event selection.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/rands-closure-dphi2.png Figure 8b : Distribution of the azimuthal separation between the $H_{\rm T}^{\rm miss}$ and the second jet in background events with QCD multi-jet events predicted directly from simulation (points, with statistical uncertainties) and as predicted by applying the rebalance and smear background determination procedure to a simulated QCD sample (shaded regions), after a modified baseline event selection.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/rands-closure-dphi3.png Figure 8c : Distribution of the azimuthal separation between the $H_{\rm T}^{\rm miss}$ and the third jet in background events with QCD multi-jet events predicted directly from simulation (points, with statistical uncertainties) and as predicted by applying the rebalance and smear background determination procedure to a simulated QCD sample (shaded regions), after a modified baseline event selection.

Revision 242017-05-20 - SamBein

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Revision 232017-05-15 - KevinPedro

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15-jet-evt-2D.png Figure 21a : Event displays for a SUSY candidate event with 15 jets in the search region, 277070:806:1490128097 in (a) $r-\phi$ view, (b) $r-\phi$ view with a white background, (c) 3D view, and (d) 3D view with a white background. The momenta of the non b-tagged jets are marked and labeled in orange and the momentum of the b-tagged jet is marked in green.
15-jet-evt-2D-white.png Figure 21b : Event displays for a SUSY candidate event with 15 jets in the search region, 277070:806:1490128097 in (a) $r-\phi$ view, (b) $r-\phi$ view with a white background, (c) 3D view, and (d) 3D view with a white background. The momenta of the non b-tagged jets are marked and labeled in orange and the momentum of the b-tagged jet is marked in green.
15-jet-evt-3D.png Figure 21c : Event displays for a SUSY candidate event with 15 jets in the search region, 277070:806:1490128097 in (a) $r-\phi$ view, (b) $r-\phi$ view with a white background, (c) 3D view, and (d) 3D view with a white background. The momenta of the non b-tagged jets are marked and labeled in orange and the momentum of the b-tagged jet is marked in green.
15-jet-evt-3D-white.png Figure 21d : Event displays for a SUSY candidate event with 15 jets in the search region, 277070:806:1490128097 in (a) $r-\phi$ view, (b) $r-\phi$ view with a white background, (c) 3D view, and (d) 3D view with a white background. The momenta of the non b-tagged jets are marked and labeled in orange and the momentum of the b-tagged jet is marked in green.
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15-jet-evt-2D.png Figure 24a : Event displays for a SUSY candidate event with 15 jets in the search region, 277070:806:1490128097 in (a) $r-\phi$ view, (b) $r-\phi$ view with a white background, (c) 3D view, and (d) 3D view with a white background. The momenta of the non b-tagged jets are marked and labeled in orange and the momentum of the b-tagged jet is marked in green.
15-jet-evt-2D-white.png Figure 24b : Event displays for a SUSY candidate event with 15 jets in the search region, 277070:806:1490128097 in (a) $r-\phi$ view, (b) $r-\phi$ view with a white background, (c) 3D view, and (d) 3D view with a white background. The momenta of the non b-tagged jets are marked and labeled in orange and the momentum of the b-tagged jet is marked in green.
15-jet-evt-3D.png Figure 24c : Event displays for a SUSY candidate event with 15 jets in the search region, 277070:806:1490128097 in (a) $r-\phi$ view, (b) $r-\phi$ view with a white background, (c) 3D view, and (d) 3D view with a white background. The momenta of the non b-tagged jets are marked and labeled in orange and the momentum of the b-tagged jet is marked in green.
15-jet-evt-3D-white.png Figure 24d : Event displays for a SUSY candidate event with 15 jets in the search region, 277070:806:1490128097 in (a) $r-\phi$ view, (b) $r-\phi$ view with a white background, (c) 3D view, and (d) 3D view with a white background. The momenta of the non b-tagged jets are marked and labeled in orange and the momentum of the b-tagged jet is marked in green.
 
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high-MHT-evt-2D.png Figure 22a : Event displays for a SUSY candidate dijet event with very high $H_{\rm T}^{\rm miss}$ in the search region, 277194:1454:2573527294 in (a) $r-\phi$ view, (b) $r-\phi$ view with a white background, (c) 3D view, and (d) 3D view with a white background. The momenta of the two jets are marked and labeled in orange.
high-MHT-evt-2D-white.png Figure 22b : Event displays for a SUSY candidate dijet event with very high $H_{\rm T}^{\rm miss}$ in the search region, 277194:1454:2573527294 in (a) $r-\phi$ view, (b) $r-\phi$ view with a white background, (c) 3D view, and (d) 3D view with a white background. The momenta of the two jets are marked and labeled in orange.
high-MHT-evt-3D.png Figure 22c : Event displays for a SUSY candidate dijet event with very high $H_{\rm T}^{\rm miss}$ in the search region, 277194:1454:2573527294 in (a) $r-\phi$ view, (b) $r-\phi$ view with a white background, (c) 3D view, and (d) 3D view with a white background. The momenta of the two jets are marked and labeled in orange.
high-MHT-evt-3D-white.png Figure 22d : Event displays for a SUSY candidate dijet event with very high $H_{\rm T}^{\rm miss}$ in the search region, 277194:1454:2573527294 in (a) $r-\phi$ view, (b) $r-\phi$ view with a white background, (c) 3D view, and (d) 3D view with a white background. The momenta of the two jets are marked and labeled in orange.
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high-MHT-evt-2D.png Figure 25a : Event displays for a SUSY candidate dijet event with very high $H_{\rm T}^{\rm miss}$ in the search region, 277194:1454:2573527294 in (a) $r-\phi$ view, (b) $r-\phi$ view with a white background, (c) 3D view, and (d) 3D view with a white background. The momenta of the two jets are marked and labeled in orange.
high-MHT-evt-2D-white.png Figure 25b : Event displays for a SUSY candidate dijet event with very high $H_{\rm T}^{\rm miss}$ in the search region, 277194:1454:2573527294 in (a) $r-\phi$ view, (b) $r-\phi$ view with a white background, (c) 3D view, and (d) 3D view with a white background. The momenta of the two jets are marked and labeled in orange.
high-MHT-evt-3D.png Figure 25c : Event displays for a SUSY candidate dijet event with very high $H_{\rm T}^{\rm miss}$ in the search region, 277194:1454:2573527294 in (a) $r-\phi$ view, (b) $r-\phi$ view with a white background, (c) 3D view, and (d) 3D view with a white background. The momenta of the two jets are marked and labeled in orange.
high-MHT-evt-3D-white.png Figure 25d : Event displays for a SUSY candidate dijet event with very high $H_{\rm T}^{\rm miss}$ in the search region, 277194:1454:2573527294 in (a) $r-\phi$ view, (b) $r-\phi$ view with a white background, (c) 3D view, and (d) 3D view with a white background. The momenta of the two jets are marked and labeled in orange.
 

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bbbb-evt-2D.png Figure 23a : Event displays for a T1bbbb-like candidate in the search region with exactly 4 jets, all of which are b-tagged, 277087:815:881281212 in (a) $r-\phi$ view, (b) $r-\phi$ view with a white background, (c) 3D view, and (d) 3D view with a white background. The momenta of the four b-tagged jets are marked and labeled in green.
bbbb-evt-2D-white.png Figure 23b : Event displays for a T1bbbb-like candidate in the search region with exactly 4 jets, all of which are b-tagged, 277087:815:881281212 in (a) $r-\phi$ view, (b) $r-\phi$ view with a white background, (c) 3D view, and (d) 3D view with a white background. The momenta of the four b-tagged jets are marked and labeled in green.
bbbb-evt-3D.png Figure 23c : Event displays for a T1bbbb-like candidate in the search region with exactly 4 jets, all of which are b-tagged, 277087:815:881281212 in (a) $r-\phi$ view, (b) $r-\phi$ view with a white background, (c) 3D view, and (d) 3D view with a white background. The momenta of the four b-tagged jets are marked and labeled in green.
bbbb-evt-3D-white.png Figure 23d : Event displays for a T1bbbb-like candidate in the search region with exactly 4 jets, all of which are b-tagged, 277087:815:881281212 in (a) $r-\phi$ view, (b) $r-\phi$ view with a white background, (c) 3D view, and (d) 3D view with a white background. The momenta of the four b-tagged jets are marked and labeled in green.
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bbbb-evt-2D.png Figure 26a : Event displays for a T1bbbb-like candidate in the search region with exactly 4 jets, all of which are b-tagged, 277087:815:881281212 in (a) $r-\phi$ view, (b) $r-\phi$ view with a white background, (c) 3D view, and (d) 3D view with a white background. The momenta of the four b-tagged jets are marked and labeled in green.
bbbb-evt-2D-white.png Figure 26b : Event displays for a T1bbbb-like candidate in the search region with exactly 4 jets, all of which are b-tagged, 277087:815:881281212 in (a) $r-\phi$ view, (b) $r-\phi$ view with a white background, (c) 3D view, and (d) 3D view with a white background. The momenta of the four b-tagged jets are marked and labeled in green.
bbbb-evt-3D.png Figure 26c : Event displays for a T1bbbb-like candidate in the search region with exactly 4 jets, all of which are b-tagged, 277087:815:881281212 in (a) $r-\phi$ view, (b) $r-\phi$ view with a white background, (c) 3D view, and (d) 3D view with a white background. The momenta of the four b-tagged jets are marked and labeled in green.
bbbb-evt-3D-white.png Figure 26d : Event displays for a T1bbbb-like candidate in the search region with exactly 4 jets, all of which are b-tagged, 277087:815:881281212 in (a) $r-\phi$ view, (b) $r-\phi$ view with a white background, (c) 3D view, and (d) 3D view with a white background. The momenta of the four b-tagged jets are marked and labeled in green.
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Revision 222017-05-15 - AndrewWhitbeck

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Revision 202017-05-11 - KevinPedro

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t1-signal-q-plot-174-bins.png Figure 15a : The sensitivity of the analysis to different direct gluino production signal models as a function of the analysis binning. The upper panel shows the total predicted SM backgrounds and the expected number of signal events in 35.9 ${\rm fb}^{-1}$ of data for six representative model points per analysis bin. The bottom panel shows the expected sensitivity, expressed in terms of the figure of merit Q, per analysis bin.
t2-signal-q-plot-174-bins.png Figure 15b : The sensitivity of the analysis to different direct squark production signal models as a function of the analysis binning. The upper panel shows the total predicted SM backgrounds and the expected number of signal events in 35.9 ${\rm fb}^{-1}$ of data for six representative model points per analysis bin. The bottom panel shows the expected sensitivity, expressed in terms of the figure of merit Q, per analysis bin.
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t1-signal-q-plot-174-bins.png Figure 18a : The sensitivity of the analysis to different direct gluino production signal models as a function of the analysis binning. The upper panel shows the total predicted SM backgrounds and the expected number of signal events in 35.9 ${\rm fb}^{-1}$ of data for six representative model points per analysis bin. The bottom panel shows the expected sensitivity, expressed in terms of the figure of merit Q, per analysis bin.
t2-signal-q-plot-174-bins.png Figure 18b : The sensitivity of the analysis to different direct squark production signal models as a function of the analysis binning. The upper panel shows the total predicted SM backgrounds and the expected number of signal events in 35.9 ${\rm fb}^{-1}$ of data for six representative model points per analysis bin. The bottom panel shows the expected sensitivity, expressed in terms of the figure of merit Q, per analysis bin.
 
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njets-projection.png Figure 16a : One-dimensional projection of observed number of events and pre-fit background predictions in the search region in $N_{\rm jet}$.
njets-projection-pull.png Figure 16b : The same distributions shown in Add. Fig. 16a, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
nbjets-projection.png Figure 16c : One-dimensional projection of observed number of events and pre-fit background predictions in the search region in $N_{\rm b-jet}$.
nbjets-projection-pull.png Figure 16d : The same distributions shown in Add. Fig. 16c, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
mht-projection.png Figure 16e : One-dimensional projection of observed number of events and pre-fit background predictions in the search region in $H_{\rm T}^{\rm miss}$.
mht-projection-pull.png Figure 16f : The same distributions shown in Add. Fig. 16e, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
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njets-projection.png Figure 19a : One-dimensional projection of observed number of events and pre-fit background predictions in the search region in $N_{\rm jet}$.
njets-projection-pull.png Figure 19b : The same distributions shown in Add. Fig. 19a, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
nbjets-projection.png Figure 19c : One-dimensional projection of observed number of events and pre-fit background predictions in the search region in $N_{\rm b-jet}$.
nbjets-projection-pull.png Figure 19d : The same distributions shown in Add. Fig. 19c, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
mht-projection.png Figure 19e : One-dimensional projection of observed number of events and pre-fit background predictions in the search region in $H_{\rm T}^{\rm miss}$.
mht-projection-pull.png Figure 19f : The same distributions shown in Add. Fig. 19e, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
 
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T1tttt-projection-pull.png Figure 17a : The same distributions shown in Fig. 11a in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
T1bbbb-projection-pull.png Figure 17b : The same distributions shown in Fig. 11b in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
T1qqqq-projection-pull.png Figure 17c : The same distributions shown in Fig. 11c in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
T2tt-projection-pull.png Figure 17d : The same distributions shown in Fig. 11d in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
T2bb-projection-pull.png Figure 17e : The same distributions shown in Fig. 11e in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
T2qq-projection-pull.png Figure 17f : The same distributions shown in Fig. 11f in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
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T1tttt-projection-pull.png Figure 20a : The same distributions shown in Fig. 11a in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
T1bbbb-projection-pull.png Figure 20b : The same distributions shown in Fig. 11b in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
T1qqqq-projection-pull.png Figure 20c : The same distributions shown in Fig. 11c in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
T2tt-projection-pull.png Figure 20d : The same distributions shown in Fig. 11d in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
T2bb-projection-pull.png Figure 20e : The same distributions shown in Fig. 11e in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
T2qq-projection-pull.png Figure 20f : The same distributions shown in Fig. 11f in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
 
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2D-T1tttt.png Figure 18a : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\rm jet}$ and $N_{\rm b-jet}$, integrated over search regions with $H_{\rm T}^{\rm miss}&amp;gt;750$ GeV and $H_{\rm T}&amp;gt;750$ GeV. An example T1tttt signal scenario with $m_{\tilde{\rm g}}=1500$ GeV and $m_{\tilde{\chi}_1^0}=100$ GeV is shown by the (stacked) purple histogram.
2D-T1tttt-pull.png Figure 18b : The same distributions shown in Add. Fig. 18a, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
2D-T1bbbb.png Figure 18c : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\rm jet}$ and $N_{\rm b-jet}$, integrated over search regions with $H_{\rm T}^{\rm miss}&amp;gt;750$ GeV and $H_{\rm T}&amp;gt;750$ GeV. An example T1bbbb signal scenario with $m_{\tilde{\rm g}}=1500$ GeV and $m_{\tilde{\chi}_1^0}=100$ GeV is shown by the (stacked) purple histogram.
2D-T1bbbb-pull.png Figure 18d : The same distributions shown in Add. Fig. 18c, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
2D-T1qqqq.png Figure 18e : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\rm jet}$ and $N_{\rm b-jet}$, integrated over search regions with $H_{\rm T}^{\rm miss}&amp;gt;750$ GeV and $H_{\rm T}&amp;gt;750$ GeV. An example T1qqqq signal scenario with $m_{\tilde{\rm g}}=1400$ GeV and $m_{\tilde{\chi}_1^0}=100$ GeV is shown by the (stacked) purple histogram.
2D-T1qqqq-pull.png Figure 18f : The same distributions shown in Add. Fig. 18e, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
2D-T2tt.png Figure 18g : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\rm jet}$ and $N_{\rm b-jet}$, integrated over search regions with $H_{\rm T}^{\rm miss}&amp;gt;750$ GeV and $H_{\rm T}&amp;gt;750$ GeV. An example T2tt signal scenario with $m_{\tilde{\rm t}}=700$ GeV and $m_{\tilde{\chi}_1^0}=50$ GeV is shown by the (stacked) purple histogram.
2D-T2tt-pull.png Figure 18h : The same distributions shown in Add. Fig. 18g, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
2D-T2bb.png Figure 18i : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\rm jet}$ and $N_{\rm b-jet}$, integrated over search regions with $H_{\rm T}^{\rm miss}&amp;gt;750$ GeV and $H_{\rm T}&amp;gt;750$ GeV. An example T2bb signal scenario with $m_{\tilde{\rm b}}=650$ GeV and $m_{\tilde{\chi}_1^0}=1$ GeV is shown by the (stacked) purple histogram.
2D-T2bb-pull.png Figure 18j : The same distributions shown in Add. Fig. 18i, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
2D-T2qq.png Figure 18k : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\rm jet}$ and $N_{\rm b-jet}$, integrated over search regions with $H_{\rm T}^{\rm miss}&amp;gt;750$ GeV and $H_{\rm T}&amp;gt;750$ GeV. An example T2qq signal scenario with $m_{\tilde{\rm b}}=1000$ GeV and $m_{\tilde{\chi}_1^0}=100$ GeV is shown by the (stacked) purple histogram.
2D-T2qq-pull.png Figure 18l : The same distributions shown in Add. Fig. 18k, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
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2D-T1tttt.png Figure 21a : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\rm jet}$ and $N_{\rm b-jet}$, integrated over search regions with $H_{\rm T}^{\rm miss}&amp;gt;750$ GeV and $H_{\rm T}&amp;gt;750$ GeV. An example T1tttt signal scenario with $m_{\tilde{\rm g}}=1500$ GeV and $m_{\tilde{\chi}_1^0}=100$ GeV is shown by the (stacked) purple histogram.
2D-T1tttt-pull.png Figure 21b : The same distributions shown in Add. Fig. 21a, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
2D-T1bbbb.png Figure 21c : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\rm jet}$ and $N_{\rm b-jet}$, integrated over search regions with $H_{\rm T}^{\rm miss}&amp;gt;750$ GeV and $H_{\rm T}&amp;gt;750$ GeV. An example T1bbbb signal scenario with $m_{\tilde{\rm g}}=1500$ GeV and $m_{\tilde{\chi}_1^0}=100$ GeV is shown by the (stacked) purple histogram.
2D-T1bbbb-pull.png Figure 21d : The same distributions shown in Add. Fig. 21c, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
2D-T1qqqq.png Figure 21e : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\rm jet}$ and $N_{\rm b-jet}$, integrated over search regions with $H_{\rm T}^{\rm miss}&amp;gt;750$ GeV and $H_{\rm T}&amp;gt;750$ GeV. An example T1qqqq signal scenario with $m_{\tilde{\rm g}}=1400$ GeV and $m_{\tilde{\chi}_1^0}=100$ GeV is shown by the (stacked) purple histogram.
2D-T1qqqq-pull.png Figure 21f : The same distributions shown in Add. Fig. 21e, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
2D-T2tt.png Figure 21g : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\rm jet}$ and $N_{\rm b-jet}$, integrated over search regions with $H_{\rm T}^{\rm miss}&amp;gt;750$ GeV and $H_{\rm T}&amp;gt;750$ GeV. An example T2tt signal scenario with $m_{\tilde{\rm t}}=700$ GeV and $m_{\tilde{\chi}_1^0}=50$ GeV is shown by the (stacked) purple histogram.
2D-T2tt-pull.png Figure 21h : The same distributions shown in Add. Fig. 21g, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
2D-T2bb.png Figure 21i : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\rm jet}$ and $N_{\rm b-jet}$, integrated over search regions with $H_{\rm T}^{\rm miss}&amp;gt;750$ GeV and $H_{\rm T}&amp;gt;750$ GeV. An example T2bb signal scenario with $m_{\tilde{\rm b}}=650$ GeV and $m_{\tilde{\chi}_1^0}=1$ GeV is shown by the (stacked) purple histogram.
2D-T2bb-pull.png Figure 21j : The same distributions shown in Add. Fig. 21i, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
2D-T2qq.png Figure 21k : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\rm jet}$ and $N_{\rm b-jet}$, integrated over search regions with $H_{\rm T}^{\rm miss}&amp;gt;750$ GeV and $H_{\rm T}&amp;gt;750$ GeV. An example T2qq signal scenario with $m_{\tilde{\rm b}}=1000$ GeV and $m_{\tilde{\chi}_1^0}=100$ GeV is shown by the (stacked) purple histogram.
2D-T2qq-pull.png Figure 21l : The same distributions shown in Add. Fig. 21k, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
 
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results-plot-prefit-35_9_pre_app-log-pulll.png Figure 19 : The same distributions shown in Fig. 9 in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
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results-plot-prefit-35_9_pre_app-log-pulll.png Figure 22 : The same distributions shown in Fig. 9 in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
 
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results-plot-prefit-12-asrs-35_9-log-pull.png Figure 20 : The same distributions shown in Fig. 10 in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
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results-plot-prefit-12-asrs-35_9-log-pull.png Figure 23 : The same distributions shown in Fig. 10 in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
 

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15-jet-evt-2D.png Figure 21a : Event displays for a SUSY candidate event with 15 jets in the search region, 277070:806:1490128097 in (a) $r-\phi$ view, (b) $r-\phi$ view with a white background, (c) 3D view, and (d) 3D view with a white background. The momenta of the non b-tagged jets are marked and labeled in orange and the momentum of the b-tagged jet is marked in green.
15-jet-evt-2D-white.png Figure 21b : Event displays for a SUSY candidate event with 15 jets in the search region, 277070:806:1490128097 in (a) $r-\phi$ view, (b) $r-\phi$ view with a white background, (c) 3D view, and (d) 3D view with a white background. The momenta of the non b-tagged jets are marked and labeled in orange and the momentum of the b-tagged jet is marked in green.
15-jet-evt-3D.png Figure 21c : Event displays for a SUSY candidate event with 15 jets in the search region, 277070:806:1490128097 in (a) $r-\phi$ view, (b) $r-\phi$ view with a white background, (c) 3D view, and (d) 3D view with a white background. The momenta of the non b-tagged jets are marked and labeled in orange and the momentum of the b-tagged jet is marked in green.
15-jet-evt-3D-white.png Figure 21d : Event displays for a SUSY candidate event with 15 jets in the search region, 277070:806:1490128097 in (a) $r-\phi$ view, (b) $r-\phi$ view with a white background, (c) 3D view, and (d) 3D view with a white background. The momenta of the non b-tagged jets are marked and labeled in orange and the momentum of the b-tagged jet is marked in green.
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15-jet-evt-2D.png Figure 21a : Event displays for a SUSY candidate event with 15 jets in the search region, 277070:806:1490128097 in (a) $r-\phi$ view, (b) $r-\phi$ view with a white background, (c) 3D view, and (d) 3D view with a white background. The momenta of the non b-tagged jets are marked and labeled in orange and the momentum of the b-tagged jet is marked in green.
15-jet-evt-2D-white.png Figure 21b : Event displays for a SUSY candidate event with 15 jets in the search region, 277070:806:1490128097 in (a) $r-\phi$ view, (b) $r-\phi$ view with a white background, (c) 3D view, and (d) 3D view with a white background. The momenta of the non b-tagged jets are marked and labeled in orange and the momentum of the b-tagged jet is marked in green.
15-jet-evt-3D.png Figure 21c : Event displays for a SUSY candidate event with 15 jets in the search region, 277070:806:1490128097 in (a) $r-\phi$ view, (b) $r-\phi$ view with a white background, (c) 3D view, and (d) 3D view with a white background. The momenta of the non b-tagged jets are marked and labeled in orange and the momentum of the b-tagged jet is marked in green.
15-jet-evt-3D-white.png Figure 21d : Event displays for a SUSY candidate event with 15 jets in the search region, 277070:806:1490128097 in (a) $r-\phi$ view, (b) $r-\phi$ view with a white background, (c) 3D view, and (d) 3D view with a white background. The momenta of the non b-tagged jets are marked and labeled in orange and the momentum of the b-tagged jet is marked in green.
 
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high-MHT-evt-2D.png Figure 22a : Event displays for a SUSY candidate dijet event with very high $H_{T}^{\rm miss}$ in the search region, 277194:1454:2573527294 in (a) $r-\phi$ view, (b) $r-\phi$ view with a white background, (c) 3D view, and (d) 3D view with a white background. The momenta of the two jets are marked and labeled in orange.
high-MHT-evt-2D-white.png Figure 22b : Event displays for a SUSY candidate dijet event with very high $H_{T}^{\rm miss}$ in the search region, 277194:1454:2573527294 in (a) $r-\phi$ view, (b) $r-\phi$ view with a white background, (c) 3D view, and (d) 3D view with a white background. The momenta of the two jets are marked and labeled in orange.
high-MHT-evt-3D.png Figure 22c : Event displays for a SUSY candidate dijet event with very high $H_{T}^{\rm miss}$ in the search region, 277194:1454:2573527294 in (a) $r-\phi$ view, (b) $r-\phi$ view with a white background, (c) 3D view, and (d) 3D view with a white background. The momenta of the two jets are marked and labeled in orange.
high-MHT-evt-3D-white.png Figure 22d : Event displays for a SUSY candidate dijet event with very high $H_{T}^{\rm miss}$ in the search region, 277194:1454:2573527294 in (a) $r-\phi$ view, (b) $r-\phi$ view with a white background, (c) 3D view, and (d) 3D view with a white background. The momenta of the two jets are marked and labeled in orange.
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high-MHT-evt-2D.png Figure 22a : Event displays for a SUSY candidate dijet event with very high $H_{\rm T}^{\rm miss}$ in the search region, 277194:1454:2573527294 in (a) $r-\phi$ view, (b) $r-\phi$ view with a white background, (c) 3D view, and (d) 3D view with a white background. The momenta of the two jets are marked and labeled in orange.
high-MHT-evt-2D-white.png Figure 22b : Event displays for a SUSY candidate dijet event with very high $H_{\rm T}^{\rm miss}$ in the search region, 277194:1454:2573527294 in (a) $r-\phi$ view, (b) $r-\phi$ view with a white background, (c) 3D view, and (d) 3D view with a white background. The momenta of the two jets are marked and labeled in orange.
high-MHT-evt-3D.png Figure 22c : Event displays for a SUSY candidate dijet event with very high $H_{\rm T}^{\rm miss}$ in the search region, 277194:1454:2573527294 in (a) $r-\phi$ view, (b) $r-\phi$ view with a white background, (c) 3D view, and (d) 3D view with a white background. The momenta of the two jets are marked and labeled in orange.
high-MHT-evt-3D-white.png Figure 22d : Event displays for a SUSY candidate dijet event with very high $H_{\rm T}^{\rm miss}$ in the search region, 277194:1454:2573527294 in (a) $r-\phi$ view, (b) $r-\phi$ view with a white background, (c) 3D view, and (d) 3D view with a white background. The momenta of the two jets are marked and labeled in orange.
 

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Search for supersymmetry in multijet events with missing transverse momentum in proton-proton collisions at 13 TeV (SUS-16-033)

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/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/zmm.png Figure 13a: The dimuon invariant mass distribution of the ${\rm Z}\rightarrow \mu^+\mu^{-}$ control region with baseline selection applied.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/zee.png Figure 13b: The dielectron invariant mass distribution of the ${\rm Z}\rightarrow e^+e^{-}$ control region with baseline selection applied.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/rzg.png Figure 14: Distribution of $R_{{\rm Z}/\gamma}$ with baseline selection applied in the 46 search bins with $N_{\rm b-jet}=0$. Points with error bars show the computed value in each bin with statistical uncertainties.
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/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/AnalysisBins_BTag0_photon_baseline_LogY.png Figure 15: Distribution of single photon event yields with baseline selection applied in the 46 search bins with $N_{\rm b-jet}=0$. Points with error bars show the observed event yields. Filled histograms show the predicted event yields from simulations.

/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/HT_photon_baseline_LogY.png Figure 16a: Distribution of single photon event yields with baseline selection applied and $N_{\rm b-jet}=0$ versus $H_{\rm T}$. Points with error bars show the observed event yields. Filled histograms show the predicted event yields from simulations.

/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/MHT_photon_baseline_LogY.png Figure 16b: Distribution of single photon event yields with baseline selection applied and $N_{\rm b-jet}=0$ versus $H^{\rm miss}_{\rm T}$. Points with error bars show the observed event yields. Filled histograms show the predicted event yields from simulations.

/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/NJets_photon_baseline_LogY.png Figure 16c: Distribution of single photon event yields with baseline selection applied and $N_{\rm b-jet}=0$ versus $N_{\rm jet}$. Points with error bars show the observed event yields. Filled histograms show the predicted event yields from simulations.

/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/PhotonPt_photon_baseline_LogY.png Figure 16d: Distribution of single photon event yields with baseline selection applied and $N_{\rm b-jet}=0$ versus $p_{\rm T,\gamma}$. Points with error bars show the observed event yields. Filled histograms show the predicted event yields from simulations.

/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/photontPurity_MHT.png Figure 17: Measured photon purity versus $H^{\rm miss}_{\rm T}$. The solid points with errors show the purity for events with a photon reconstructed in the barrel; open points with errors show the purity for events with a photon reconstructed in the endcap.
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Results: yields vs. background prediction, select kinematic distributions

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Revision 182017-05-10 - JohnBradmillerFeld

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META TOPICPARENT name="RA2b13TeV"

Search for supersymmetry in multijet events with missing transverse momentum in proton-proton collisions at 13 TeV (SUS-16-033)

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Figure Caption
15-jet-evt-2D.png Figure 21a : Event displays for a SUSY candidate event with 15 jets in the search region, 277070:806:1490128097 in (a) $r-\phi$ view, (b) $r-\phi$ view with a white background, (c) 3D view, and (d) 3D view with a white background. The momenta of the non b-tagged jets are marked and labeled in orange and the momentum of the b-tagged jet is marked in green.
15-jet-evt-2D-white.png Figure 21b : Event displays for a SUSY candidate event with 15 jets in the search region, 277070:806:1490128097 in (a) $r-\phi$ view, (b) $r-\phi$ view with a white background, (c) 3D view, and (d) 3D view with a white background. The momenta of the non b-tagged jets are marked and labeled in orange and the momentum of the b-tagged jet is marked in green.
15-jet-evt-3D.png Figure 21c : Event displays for a SUSY candidate event with 15 jets in the search region, 277070:806:1490128097 in (a) $r-\phi$ view, (b) $r-\phi$ view with a white background, (c) 3D view, and (d) 3D view with a white background. The momenta of the non b-tagged jets are marked and labeled in orange and the momentum of the b-tagged jet is marked in green.
15-jet-evt-3D-white.png Figure 21d : Event displays for a SUSY candidate event with 15 jets in the search region, 277070:806:1490128097 in (a) $r-\phi$ view, (b) $r-\phi$ view with a white background, (c) 3D view, and (d) 3D view with a white background. The momenta of the non b-tagged jets are marked and labeled in orange and the momentum of the b-tagged jet is marked in green.

Figure Caption
high-MHT-evt-2D.png Figure 22a : Event displays for a SUSY candidate dijet event with very high $H_{T}^{\rm miss}$ in the search region, 277194:1454:2573527294 in (a) $r-\phi$ view, (b) $r-\phi$ view with a white background, (c) 3D view, and (d) 3D view with a white background. The momenta of the two jets are marked and labeled in orange.
high-MHT-evt-2D-white.png Figure 22b : Event displays for a SUSY candidate dijet event with very high $H_{T}^{\rm miss}$ in the search region, 277194:1454:2573527294 in (a) $r-\phi$ view, (b) $r-\phi$ view with a white background, (c) 3D view, and (d) 3D view with a white background. The momenta of the two jets are marked and labeled in orange.
high-MHT-evt-3D.png Figure 22c : Event displays for a SUSY candidate dijet event with very high $H_{T}^{\rm miss}$ in the search region, 277194:1454:2573527294 in (a) $r-\phi$ view, (b) $r-\phi$ view with a white background, (c) 3D view, and (d) 3D view with a white background. The momenta of the two jets are marked and labeled in orange.
high-MHT-evt-3D-white.png Figure 22d : Event displays for a SUSY candidate dijet event with very high $H_{T}^{\rm miss}$ in the search region, 277194:1454:2573527294 in (a) $r-\phi$ view, (b) $r-\phi$ view with a white background, (c) 3D view, and (d) 3D view with a white background. The momenta of the two jets are marked and labeled in orange.

Figure Caption
bbbb-evt-2D.png Figure 23a : Event displays for a T1bbbb-like candidate in the search region with exactly 4 jets, all of which are b-tagged, 277087:815:881281212 in (a) $r-\phi$ view, (b) $r-\phi$ view with a white background, (c) 3D view, and (d) 3D view with a white background. The momenta of the four b-tagged jets are marked and labeled in green.
bbbb-evt-2D-white.png Figure 23b : Event displays for a T1bbbb-like candidate in the search region with exactly 4 jets, all of which are b-tagged, 277087:815:881281212 in (a) $r-\phi$ view, (b) $r-\phi$ view with a white background, (c) 3D view, and (d) 3D view with a white background. The momenta of the four b-tagged jets are marked and labeled in green.
bbbb-evt-3D.png Figure 23c : Event displays for a T1bbbb-like candidate in the search region with exactly 4 jets, all of which are b-tagged, 277087:815:881281212 in (a) $r-\phi$ view, (b) $r-\phi$ view with a white background, (c) 3D view, and (d) 3D view with a white background. The momenta of the four b-tagged jets are marked and labeled in green.
bbbb-evt-3D-white.png Figure 23d : Event displays for a T1bbbb-like candidate in the search region with exactly 4 jets, all of which are b-tagged, 277087:815:881281212 in (a) $r-\phi$ view, (b) $r-\phi$ view with a white background, (c) 3D view, and (d) 3D view with a white background. The momenta of the four b-tagged jets are marked and labeled in green.

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Revision 172017-05-09 - TroyMulholland

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META TOPICPARENT name="RA2b13TeV"

Search for supersymmetry in multijet events with missing transverse momentum in proton-proton collisions at 13 TeV (SUS-16-033)

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Revision 162017-05-09 - KevinPedro

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Search for supersymmetry in multijet events with missing transverse momentum in proton-proton collisions at 13 TeV (SUS-16-033)

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/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/supPredInferred2016LDPNJetsc3.png Figure 10a : Distributions of the multiplicity of jets as observed (points, with statistical uncertainties) and as predicted by applying the data-driven methods of background determination (shaded distributions with statistical and systematic uncertainties added in quadrature), in the low-$H_{\rm T}^{\rm miss}$, inverted $\Delta\phi$ control region.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/supPredInferred2016LDPBTagsc3.png Figure 10b : Distributions of the multiplicity of b-tagged jets as observed (points, with statistical uncertainties) and as predicted by applying the data-driven methods of background determination (shaded distributions with statistical and systematic uncertainties added in quadrature), in the low-$H_{\rm T}^{\rm miss}$, inverted $\Delta\phi$ control region.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/sup_PullLdp.png Figure 10c : The distribution of the significance of deviation between the QCD prediction and inferred QCD count in the 174 inverted $\Delta\phi$ signal region bins. Here, the inferred QCD count is the observed count minus the predicted electroweak background count.
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/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/sr-ht.png Figure 11a : Distribution of $R_{Z\rightarrow \ell^+\ell^{-}/\gamma}$ vs. $H_{\rm T}$ with baseline selection applied. Points with error bars show the computed value in each bin with statistical uncertainties.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/sr-mht.png Figure 11b : Distribution of $R_{Z\rightarrow \ell^+\ell^{-}/\gamma}$ vs. $H_{\rm T}^{\rm miss}$ with baseline selection applied. Points with error bars show the computed value in each bin with statistical uncertainties.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/sr-nj.png Figure 11c : Distribution of $R_{Z\rightarrow \ell^+\ell^{-}/\gamma}$ vs. $N_{\rm jet}$ with baseline selection applied. Points with error bars show the computed value in each bin with statistical uncertainties.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/dr-ht.png Figure 12a: Distribution of $\frac{R_{Z\rightarrow \ell^+\ell^{-}/\gamma}^{\rm Data}}{R_{Z\rightarrow \ell^+\ell^{-}/\gamma}^{\rm Sim}}$ vs. $H_{\rm T}$ with baseline selection applied. Points with error bars show the computed value in each bin with statistical uncertainties. The solid blue line shows the straight-line fit, with the uncertainties propagated as blue dashed lines.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/dr-mht.png Figure 12b: Distribution of $\frac{R_{Z\rightarrow \ell^+\ell^{-}/\gamma}^{\rm Data}}{R_{Z\rightarrow \ell^+\ell^{-}/\gamma}^{\rm Sim}}$ vs. $H_{\rm T}^{\rm miss}$ with baseline selection applied. Points with error bars show the computed value in each bin with statistical uncertainties. The solid blue line shows the straight-line fit, with the uncertainties propagated as blue dashed lines.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/dr-nj.png Figure 12c: Distribution of $\frac{R_{Z\rightarrow \ell^+\ell^{-}/\gamma}^{\rm Data}}{R_{Z\rightarrow \ell^+\ell^{-}/\gamma}^{\rm Sim}}$ vs. $N_{\rm jet}$ with baseline selection applied. Points with error bars show the computed value in each bin with statistical uncertainties. The solid blue line shows the straight-line fit, with the uncertainties propagated as blue dashed lines.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/zmm.png Figure 13a: The dimuon invariant mass distribution of the $Z\rightarrow \mu^+\mu^{-}$ control region with baseline selection applied.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/zee.png Figure 13b: The dielectron invariant mass distribution of the $Z\rightarrow e^+e^{-}$ control region with baseline selection applied.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/rzg.png Figure 14: Distribution of $R_{Z/\gamma}$ with baseline selection applied in the 46 search bins with $N_{\rm b-jet}=0$. Points with error bars show the computed value in each bin with statistical uncertainties.
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/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/sr-ht.png Figure 11a : Distribution of $R_{{\rm Z}\rightarrow \ell^+\ell^{-}/\gamma}$ vs. $H_{\rm T}$ with baseline selection applied. Points with error bars show the computed value in each bin with statistical uncertainties.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/sr-mht.png Figure 11b : Distribution of $R_{{\rm Z}\rightarrow \ell^+\ell^{-}/\gamma}$ vs. $H_{\rm T}^{\rm miss}$ with baseline selection applied. Points with error bars show the computed value in each bin with statistical uncertainties.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/sr-nj.png Figure 11c : Distribution of $R_{{\rm Z}\rightarrow \ell^+\ell^{-}/\gamma}$ vs. $N_{\rm jet}$ with baseline selection applied. Points with error bars show the computed value in each bin with statistical uncertainties.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/dr-ht.png Figure 12a: Distribution of $\frac{R_{{\rm Z}\rightarrow \ell^+\ell^{-}/\gamma}^{\rm Data}}{R_{{\rm Z}\rightarrow \ell^+\ell^{-}/\gamma}^{\rm Sim}}$ vs. $H_{\rm T}$ with baseline selection applied. Points with error bars show the computed value in each bin with statistical uncertainties. The solid blue line shows the straight-line fit, with the uncertainties propagated as blue dashed lines.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/dr-mht.png Figure 12b: Distribution of $\frac{R_{{\rm Z}\rightarrow \ell^+\ell^{-}/\gamma}^{\rm Data}}{R_{{\rm Z}\rightarrow \ell^+\ell^{-}/\gamma}^{\rm Sim}}$ vs. $H_{\rm T}^{\rm miss}$ with baseline selection applied. Points with error bars show the computed value in each bin with statistical uncertainties. The solid blue line shows the straight-line fit, with the uncertainties propagated as blue dashed lines.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/dr-nj.png Figure 12c: Distribution of $\frac{R_{{\rm Z}\rightarrow \ell^+\ell^{-}/\gamma}^{\rm Data}}{R_{{\rm Z}\rightarrow \ell^+\ell^{-}/\gamma}^{\rm Sim}}$ vs. $N_{\rm jet}$ with baseline selection applied. Points with error bars show the computed value in each bin with statistical uncertainties. The solid blue line shows the straight-line fit, with the uncertainties propagated as blue dashed lines.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/zmm.png Figure 13a: The dimuon invariant mass distribution of the ${\rm Z}\rightarrow \mu^+\mu^{-}$ control region with baseline selection applied.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/zee.png Figure 13b: The dielectron invariant mass distribution of the ${\rm Z}\rightarrow e^+e^{-}$ control region with baseline selection applied.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/rzg.png Figure 14: Distribution of $R_{{\rm Z}/\gamma}$ with baseline selection applied in the 46 search bins with $N_{\rm b-jet}=0$. Points with error bars show the computed value in each bin with statistical uncertainties.
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Results: yields vs. background prediction, select kinematic distributions

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t1-signal-q-plot-174-bins.png Figure 11e : The sensitivity of the analysis to different direct gluino production signal models as a function of the analysis binning. The upper panel shows the total predicted SM backgrounds and the expected number of signal events in 35.9 ${\rm fb}^{-1}$ of data for six representative model points per analysis bin. The bottom panel shows the expected sensitivity, expressed in terms of the figure of merit Q, per analysis bin.
t2-signal-q-plot-174-bins.png Figure 11e : The sensitivity of the analysis to different direct squark production signal models as a function of the analysis binning. The upper panel shows the total predicted SM backgrounds and the expected number of signal events in 35.9 ${\rm fb}^{-1}$ of data for six representative model points per analysis bin. The bottom panel shows the expected sensitivity, expressed in terms of the figure of merit Q, per analysis bin.
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t1-signal-q-plot-174-bins.png Figure 15a : The sensitivity of the analysis to different direct gluino production signal models as a function of the analysis binning. The upper panel shows the total predicted SM backgrounds and the expected number of signal events in 35.9 ${\rm fb}^{-1}$ of data for six representative model points per analysis bin. The bottom panel shows the expected sensitivity, expressed in terms of the figure of merit Q, per analysis bin.
t2-signal-q-plot-174-bins.png Figure 15b : The sensitivity of the analysis to different direct squark production signal models as a function of the analysis binning. The upper panel shows the total predicted SM backgrounds and the expected number of signal events in 35.9 ${\rm fb}^{-1}$ of data for six representative model points per analysis bin. The bottom panel shows the expected sensitivity, expressed in terms of the figure of merit Q, per analysis bin.
 
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njets-projection.png Figure 12a : One-dimensional projection of observed number of events and pre-fit background predictions in the search region in $N_{\rm jet}$.
njets-projection-pull.png Figure 12b : The same distributions shown in Add. Fig. 12a, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
nbjets-projection.png Figure 12c : One-dimensional projection of observed number of events and pre-fit background predictions in the search region in $N_{\rm b-jet}$.
nbjets-projection-pull.png Figure 12d : The same distributions shown in Add. Fig. 12c, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
mht-projection.png Figure 12e : One-dimensional projection of observed number of events and pre-fit background predictions in the search region in $H_{\rm T}^{\rm miss}$.
mht-projection-pull.png Figure 12f : The same distributions shown in Add. Fig. 12e, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
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njets-projection.png Figure 16a : One-dimensional projection of observed number of events and pre-fit background predictions in the search region in $N_{\rm jet}$.
njets-projection-pull.png Figure 16b : The same distributions shown in Add. Fig. 16a, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
nbjets-projection.png Figure 16c : One-dimensional projection of observed number of events and pre-fit background predictions in the search region in $N_{\rm b-jet}$.
nbjets-projection-pull.png Figure 16d : The same distributions shown in Add. Fig. 16c, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
mht-projection.png Figure 16e : One-dimensional projection of observed number of events and pre-fit background predictions in the search region in $H_{\rm T}^{\rm miss}$.
mht-projection-pull.png Figure 16f : The same distributions shown in Add. Fig. 16e, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
 
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T1tttt-projection-pull.png Figure 13a : The same distributions shown in Fig. 11a in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
T1bbbb-projection-pull.png Figure 13b : The same distributions shown in Fig. 11b in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
T1qqqq-projection-pull.png Figure 13c : The same distributions shown in Fig. 11c in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
T2tt-projection-pull.png Figure 13d : The same distributions shown in Fig. 11d in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
T2bb-projection-pull.png Figure 13e : The same distributions shown in Fig. 11e in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
T2qq-projection-pull.png Figure 13f : The same distributions shown in Fig. 11f in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
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T1tttt-projection-pull.png Figure 17a : The same distributions shown in Fig. 11a in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
T1bbbb-projection-pull.png Figure 17b : The same distributions shown in Fig. 11b in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
T1qqqq-projection-pull.png Figure 17c : The same distributions shown in Fig. 11c in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
T2tt-projection-pull.png Figure 17d : The same distributions shown in Fig. 11d in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
T2bb-projection-pull.png Figure 17e : The same distributions shown in Fig. 11e in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
T2qq-projection-pull.png Figure 17f : The same distributions shown in Fig. 11f in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
 
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2D-T1tttt.png Figure 14a : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\rm jet}$ and $N_{\rm b-jet}$, integrated over search regions with $H_{\rm T}^{\rm miss}&amp;gt;750$ GeV and $H_{\rm T}&amp;gt;750$ GeV. An example T1tttt signal scenario with $m_{\tilde{\rm g}}=1500$ GeV and $m_{\tilde{\chi}_1^0}=100$ GeV is shown by the (stacked) purple histogram.
2D-T1tttt-pull.png Figure 14b : The same distributions shown in Add. Fig. 14a, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
2D-T1bbbb.png Figure 14c : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\rm jet}$ and $N_{\rm b-jet}$, integrated over search regions with $H_{\rm T}^{\rm miss}&amp;gt;750$ GeV and $H_{\rm T}&amp;gt;750$ GeV. An example T1bbbb signal scenario with $m_{\tilde{\rm g}}=1500$ GeV and $m_{\tilde{\chi}_1^0}=100$ GeV is shown by the (stacked) purple histogram.
2D-T1bbbb-pull.png Figure 14d : The same distributions shown in Add. Fig. 14c, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
2D-T1qqqq.png Figure 14e : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\rm jet}$ and $N_{\rm b-jet}$, integrated over search regions with $H_{\rm T}^{\rm miss}&amp;gt;750$ GeV and $H_{\rm T}&amp;gt;750$ GeV. An example T1qqqq signal scenario with $m_{\tilde{\rm g}}=1400$ GeV and $m_{\tilde{\chi}_1^0}=100$ GeV is shown by the (stacked) purple histogram.
2D-T1qqqq-pull.png Figure 14f : The same distributions shown in Add. Fig. 14e, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
2D-T2tt.png Figure 14g : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\rm jet}$ and $N_{\rm b-jet}$, integrated over search regions with $H_{\rm T}^{\rm miss}&amp;gt;750$ GeV and $H_{\rm T}&amp;gt;750$ GeV. An example T2tt signal scenario with $m_{\tilde{\rm t}}=700$ GeV and $m_{\tilde{\chi}_1^0}=50$ GeV is shown by the (stacked) purple histogram.
2D-T2tt-pull.png Figure 14h : The same distributions shown in Add. Fig. 14g, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
2D-T2bb.png Figure 14i : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\rm jet}$ and $N_{\rm b-jet}$, integrated over search regions with $H_{\rm T}^{\rm miss}&amp;gt;750$ GeV and $H_{\rm T}&amp;gt;750$ GeV. An example T2bb signal scenario with $m_{\tilde{\rm b}}=650$ GeV and $m_{\tilde{\chi}_1^0}=1$ GeV is shown by the (stacked) purple histogram.
2D-T2bb-pull.png Figure 14j : The same distributions shown in Add. Fig. 14i, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
2D-T2qq.png Figure 14k : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\rm jet}$ and $N_{\rm b-jet}$, integrated over search regions with $H_{\rm T}^{\rm miss}&amp;gt;750$ GeV and $H_{\rm T}&amp;gt;750$ GeV. An example T2qq signal scenario with $m_{\tilde{\rm b}}=1000$ GeV and $m_{\tilde{\chi}_1^0}=100$ GeV is shown by the (stacked) purple histogram.
2D-T2qq-pull.png Figure 14l : The same distributions shown in Add. Fig. 14k, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
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2D-T1tttt.png Figure 18a : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\rm jet}$ and $N_{\rm b-jet}$, integrated over search regions with $H_{\rm T}^{\rm miss}&amp;gt;750$ GeV and $H_{\rm T}&amp;gt;750$ GeV. An example T1tttt signal scenario with $m_{\tilde{\rm g}}=1500$ GeV and $m_{\tilde{\chi}_1^0}=100$ GeV is shown by the (stacked) purple histogram.
2D-T1tttt-pull.png Figure 18b : The same distributions shown in Add. Fig. 18a, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
2D-T1bbbb.png Figure 18c : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\rm jet}$ and $N_{\rm b-jet}$, integrated over search regions with $H_{\rm T}^{\rm miss}&amp;gt;750$ GeV and $H_{\rm T}&amp;gt;750$ GeV. An example T1bbbb signal scenario with $m_{\tilde{\rm g}}=1500$ GeV and $m_{\tilde{\chi}_1^0}=100$ GeV is shown by the (stacked) purple histogram.
2D-T1bbbb-pull.png Figure 18d : The same distributions shown in Add. Fig. 18c, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
2D-T1qqqq.png Figure 18e : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\rm jet}$ and $N_{\rm b-jet}$, integrated over search regions with $H_{\rm T}^{\rm miss}&amp;gt;750$ GeV and $H_{\rm T}&amp;gt;750$ GeV. An example T1qqqq signal scenario with $m_{\tilde{\rm g}}=1400$ GeV and $m_{\tilde{\chi}_1^0}=100$ GeV is shown by the (stacked) purple histogram.
2D-T1qqqq-pull.png Figure 18f : The same distributions shown in Add. Fig. 18e, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
2D-T2tt.png Figure 18g : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\rm jet}$ and $N_{\rm b-jet}$, integrated over search regions with $H_{\rm T}^{\rm miss}&amp;gt;750$ GeV and $H_{\rm T}&amp;gt;750$ GeV. An example T2tt signal scenario with $m_{\tilde{\rm t}}=700$ GeV and $m_{\tilde{\chi}_1^0}=50$ GeV is shown by the (stacked) purple histogram.
2D-T2tt-pull.png Figure 18h : The same distributions shown in Add. Fig. 18g, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
2D-T2bb.png Figure 18i : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\rm jet}$ and $N_{\rm b-jet}$, integrated over search regions with $H_{\rm T}^{\rm miss}&amp;gt;750$ GeV and $H_{\rm T}&amp;gt;750$ GeV. An example T2bb signal scenario with $m_{\tilde{\rm b}}=650$ GeV and $m_{\tilde{\chi}_1^0}=1$ GeV is shown by the (stacked) purple histogram.
2D-T2bb-pull.png Figure 18j : The same distributions shown in Add. Fig. 18i, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
2D-T2qq.png Figure 18k : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\rm jet}$ and $N_{\rm b-jet}$, integrated over search regions with $H_{\rm T}^{\rm miss}&amp;gt;750$ GeV and $H_{\rm T}&amp;gt;750$ GeV. An example T2qq signal scenario with $m_{\tilde{\rm b}}=1000$ GeV and $m_{\tilde{\chi}_1^0}=100$ GeV is shown by the (stacked) purple histogram.
2D-T2qq-pull.png Figure 18l : The same distributions shown in Add. Fig. 18k, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
 
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results-plot-prefit-35_9_pre_app-log-pulll.png Figure 15 : The same distributions shown in Fig. 9 in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
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results-plot-prefit-35_9_pre_app-log-pulll.png Figure 19 : The same distributions shown in Fig. 9 in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
 
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results-plot-prefit-12-asrs-35_9-log-pull.png Figure 16 : The same distributions shown in Fig. 10 in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
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results-plot-prefit-12-asrs-35_9-log-pull.png Figure 20 : The same distributions shown in Fig. 10 in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
 

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Search for supersymmetry in multijet events with missing transverse momentum in proton-proton collisions at 13 TeV (SUS-16-033)

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/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/supPredInferred2016LDPNJetsc3.png Figure 10a : Distributions of the multiplicity of jets as observed (points, with statistical uncertainties) and as predicted by applying the data-driven methods of background determination (shaded distributions with statistical and systematic uncertainties added in quadrature), in the low-$H_{\rm T}^{\rm miss}$, inverted $\Delta\phi$ control region.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/supPredInferred2016LDPBTagsc3.png Figure 10b : Distributions of the multiplicity of b-tagged jets as observed (points, with statistical uncertainties) and as predicted by applying the data-driven methods of background determination (shaded distributions with statistical and systematic uncertainties added in quadrature), in the low-$H_{\rm T}^{\rm miss}$, inverted $\Delta\phi$ control region.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/sup_PullLdp.png Figure 10c : The distribution of the significance of deviation between the QCD prediction and inferred QCD count in the 174 inverted $\Delta\phi$ signal region bins. Here, the inferred QCD count is the observed count minus the predicted electroweak background count.
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/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/sr-ht.png Figure 11a : Distribution of $R_{Z\rightarrow \ell^+\ell^{-}/\gamma}$ vs. $H_{\rm T}$ with baseline selection applied. Points with error bars show the computed value in each bin with statistical uncertainties.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/sr-mht.png Figure 11b : Distribution of $R_{Z\rightarrow \ell^+\ell^{-}/\gamma}$ vs. $H_{\rm T}^{\rm miss}$ with baseline selection applied. Points with error bars show the computed value in each bin with statistical uncertainties.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/sr-nj.png Figure 11c : Distribution of $R_{Z\rightarrow \ell^+\ell^{-}/\gamma}$ vs. $N_{\rm jet}$ with baseline selection applied. Points with error bars show the computed value in each bin with statistical uncertainties.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/dr-ht.png Figure 12a: Distribution of $\frac{R_{Z\rightarrow \ell^+\ell^{-}/\gamma}^{\rm Data}}{R_{Z\rightarrow \ell^+\ell^{-}/\gamma}^{\rm Sim}}$ vs. $H_{\rm T}$ with baseline selection applied. Points with error bars show the computed value in each bin with statistical uncertainties. The solid blue line shows the straight-line fit, with the uncertainties propagated as blue dashed lines.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/dr-mht.png Figure 12b: Distribution of $\frac{R_{Z\rightarrow \ell^+\ell^{-}/\gamma}^{\rm Data}}{R_{Z\rightarrow \ell^+\ell^{-}/\gamma}^{\rm Sim}}$ vs. $H_{\rm T}^{\rm miss}$ with baseline selection applied. Points with error bars show the computed value in each bin with statistical uncertainties. The solid blue line shows the straight-line fit, with the uncertainties propagated as blue dashed lines.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/dr-nj.png Figure 12c: Distribution of $\frac{R_{Z\rightarrow \ell^+\ell^{-}/\gamma}^{\rm Data}}{R_{Z\rightarrow \ell^+\ell^{-}/\gamma}^{\rm Sim}}$ vs. $N_{\rm jet}$ with baseline selection applied. Points with error bars show the computed value in each bin with statistical uncertainties. The solid blue line shows the straight-line fit, with the uncertainties propagated as blue dashed lines.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/zmm.png Figure 13a: The dimuon invariant mass distribution of the $Z\rightarrow \mu^+\mu^{-}$ control region with baseline selection applied.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/zee.png Figure 13b: The dielectron invariant mass distribution of the $Z\rightarrow e^+e^{-}$ control region with baseline selection applied.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/rzg.png Figure 14: Distribution of $R_{Z/\gamma}$ with baseline selection applied in the 46 search bins with $N_{\rm b-jet}=0$. Points with error bars show the computed value in each bin with statistical uncertainties.
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Results: yields vs. background prediction, select kinematic distributions

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Revision 142017-05-05 - SamBein

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META TOPICPARENT name="RA2b13TeV"

Search for supersymmetry in multijet events with missing transverse momentum in proton-proton collisions at 13 TeV (SUS-16-033)

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Revision 132017-05-04 - JohnBradmillerFeld

Line: 1 to 1
 
META TOPICPARENT name="RA2b13TeV"

Search for supersymmetry in multijet events with missing transverse momentum in proton-proton collisions at 13 TeV (SUS-16-033)

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2D-T2qq.png Figure 14k : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\rm jet}$ and $N_{\rm b-jet}$, integrated over search regions with $H_{\rm T}^{\rm miss}&amp;gt;750$ GeV and $H_{\rm T}&amp;gt;750$ GeV. An example T2qq signal scenario with $m_{\tilde{\rm b}}=1000$ GeV and $m_{\tilde{\chi}_1^0}=100$ GeV is shown by the (stacked) purple histogram.
2D-T2qq-pull.png Figure 14l : The same distributions shown in Add. Fig. 14k, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
Added:
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Figure Caption
results-plot-prefit-35_9_pre_app-log-pulll.png Figure 15 : The same distributions shown in Fig. 9 in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.

Figure Caption
results-plot-prefit-12-asrs-35_9-log-pull.png Figure 16 : The same distributions shown in Fig. 10 in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
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Revision 122017-05-04 - SamBein

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META TOPICPARENT name="RA2b13TeV"

Search for supersymmetry in multijet events with missing transverse momentum in proton-proton collisions at 13 TeV (SUS-16-033)

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PClosure_MHT_delphi_stacked_ARElog116_ARElog115_Plot_kRed-9.png Figure 6b : Distributions of $H_{\rm T}^{\rm miss}$ in background events with a hadronically decaying $\tau$ lepton as predicted directly from simulation (points, with statistical uncertainties) and as predicted by applying the hadronically decaying $\tau$ lepton background determination procedure to simulated muon control sample (shaded regions), for the baseline selection. The simulation includes ttbar, W+jets, and single top quark process events.
PClosure_NJet_delphi_stacked_ARElog116_ARElog115_Plot_kRed-9.png Figure 6c : Distributions of the number of jets in background events with a hadronically decaying $\tau$ lepton as predicted directly from simulation (points, with statistical uncertainties) and as predicted by applying the hadronically decaying $\tau$ lepton background determination procedure to simulated muon control sample (shaded regions), for the baseline selection. The simulation includes ttbar, W+jets, and single top quark process events.
PClosure_NBtag_delphi_stacked_ARElog116_ARElog115_Plot_kRed-9.png Figure 6d : Distributions of the number of b-tagged jets in background events with a hadronically decaying $\tau$ lepton as predicted directly from simulation (points, with statistical uncertainties) and as predicted by applying the hadronically decaying $\tau$ lepton background determination procedure to simulated muon control sample (shaded regions), for the baseline selection. The simulation includes ttbar, W+jets, and single top quark process events.
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/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/rands-closure-ht.png Figure 7a : Distributions of $H_{\rm T}$ in background events with a hadronically decaying $\tau$ lepton as predicted directly from simulation (points, with statistical uncertainties) and as predicted by applying the hadronically decaying $\tau$ lepton background determination procedure to simulated muon control sample (shaded regions), for the baseline selection. The simulation includes ttbar, W+jets, and single top quark process events.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/rands-closure-mht.png Figure 7b : Distributions of $H_{\rm T}^{\rm miss}$ in background events with a hadronically decaying $\tau$ lepton as predicted directly from simulation (points, with statistical uncertainties) and as predicted by applying the hadronically decaying $\tau$ lepton background determination procedure to simulated muon control sample (shaded regions), for the baseline selection. The simulation includes ttbar, W+jets, and single top quark process events.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/rands-closure-njets.png Figure 7c : Distributions of the number of jets in background events with a hadronically decaying $\tau$ lepton as predicted directly from simulation (points, with statistical uncertainties) and as predicted by applying the hadronically decaying $\tau$ lepton background determination procedure to simulated muon control sample (shaded regions), for the baseline selection. The simulation includes ttbar, W+jets, and single top quark process events.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/rands-closure-btags.png Figure 7d : Distributions of the number of b-tagged jets in background events with a hadronically decaying $\tau$ lepton as predicted directly from simulation (points, with statistical uncertainties) and as predicted by applying the hadronically decaying $\tau$ lepton background determination procedure to simulated muon control sample (shaded regions), for the baseline selection. The simulation includes ttbar, W+jets, and single top quark process events.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/rands-closure-dphi1.png Figure 8a : Distributions of the azimuthal separation between the $H_{\rm T}^{\rm miss}$ and the first jet in QCD background events as predicted directly from simulation (points, with statistical uncertainties) and as predicted by applying the rebalance and smear background determination procedure to a simulated QCD sample (shaded distributions with statistical and systematic uncertainties added in quadrature), for a QCD-enhanced modified baseline selection.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/rands-closure-dphi2.png Figure 8b : Distributions of the azimuthal separation between the $H_{\rm T}^{\rm miss}$ and the second jet in QCD background events as predicted directly from simulation (points, with statistical uncertainties) and as predicted by applying the rebalance and smear background determination procedure to a simulated QCD sample (shaded distributions with statistical and systematic uncertainties added in quadrature), for a QCD-enhanced modified baseline selection.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/rands-closure-dphi3.png Figure 8c : Distributions of the azimuthal separation between the $H_{\rm T}^{\rm miss}$ and the third jet in QCD background events as predicted directly from simulation (points, with statistical uncertainties) and as predicted by applying the rebalance and smear background determination procedure to a simulated QCD sample (shaded distributions with statistical and systematic uncertainties added in quadrature), for a QCD-enhanced modified baseline selection.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/rands-closure-dphi4.png Figure 8d : Distributions of the azimuthal separation between the $H_{\rm T}^{\rm miss}$ and the fourth jet in QCD background events as predicted directly from simulation (points, with statistical uncertainties) and as predicted by applying the rebalance and smear background determination procedure to a simulated QCD sample (shaded distributions with statistical and systematic uncertainties added in quadrature), for a QCD-enhanced modified baseline selection.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/supMoriondLdpNJets_HTMHT3.png Figure 9a : Distributions of the multiplicity of jets as observed (points, with statistical uncertainties) and as predicted by applying the data-driven methods of background determination (shaded distributions with statistical and systematic uncertainties added in quadrature), in various control regions with the inverted $\Delta\phi$ selection applied to enhance the QCD yield.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/supMoriondLdpNJets_HTMHT6.png Figure 9b: Distributions of the multiplicity of jets as observed (points, with statistical uncertainties) and as predicted by applying the data-driven methods of background determination (shaded distributions with statistical and systematic uncertainties added in quadrature), in various control regions with the inverted $\Delta\phi$ selection applied to enhance the QCD yield.
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/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/rands-closure-ht.png Figure 7a : Distribution of $H_{\rm T}$ in background events with QCD multi-jet events predicted directly from simulation (points, with statistical uncertainties) and as predicted by applying the rebalance and smear background determination procedure to a simulated QCD sample (shaded regions), after a modified baseline event selection.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/rands-closure-mht.png Figure 7b : Distribution of $H_{\rm T}^{\rm miss}$ in background events with QCD multi-jet events predicted directly from simulation (points, with statistical uncertainties) and as predicted by applying the rebalance and smear background determination procedure to a simulated QCD sample (shaded regions), after a modified baseline event selection.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/rands-closure-njets.png Figure 7c : Distribution of the number of jets in background events with QCD multi-jet events predicted directly from simulation (points, with statistical uncertainties) and as predicted by applying the rebalance and smear background determination procedure to a simulated QCD sample (shaded regions), after a modified baseline event selection.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/rands-closure-btags.png Figure 7d : Distribution of the number of b-tagged jetsin background events with QCD multi-jet events predicted directly from simulation (points, with statistical uncertainties) and as predicted by applying the rebalance and smear background determination procedure to a simulated QCD sample (shaded regions), after a modified baseline event selection.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/rands-closure-dphi1.png Figure 8a : Distribution of the azimuthal separation between the $H_{\rm T}^{\rm miss}$ and the first jet in background events with QCD multi-jet events predicted directly from simulation (points, with statistical uncertainties) and as predicted by applying the rebalance and smear background determination procedure to a simulated QCD sample (shaded regions), after a modified baseline event selection.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/rands-closure-dphi2.png Figure 8b : Distribution of the azimuthal separation between the $H_{\rm T}^{\rm miss}$ and the second jet in background events with QCD multi-jet events predicted directly from simulation (points, with statistical uncertainties) and as predicted by applying the rebalance and smear background determination procedure to a simulated QCD sample (shaded regions), after a modified baseline event selection.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/rands-closure-dphi3.png Figure 8c : Distribution of the azimuthal separation between the $H_{\rm T}^{\rm miss}$ and the third jet in background events with QCD multi-jet events predicted directly from simulation (points, with statistical uncertainties) and as predicted by applying the rebalance and smear background determination procedure to a simulated QCD sample (shaded regions), after a modified baseline event selection.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/rands-closure-dphi4.png Figure 8d : Distribution of the azimuthal separation between the $H_{\rm T}^{\rm miss}$ and the fourth jet in background events with QCD multi-jet events predicted directly from simulation (points, with statistical uncertainties) and as predicted by applying the rebalance and smear background determination procedure to a simulated QCD sample (shaded regions), after a modified baseline event selection.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/supMoriondLdpNJets_HTMHT3.png Figure 9a : Distribution of the multiplicity of jets as observed (points, with statistical uncertainties) and as predicted by applying the data-driven methods of background determination (shaded distributions with statistical and systematic uncertainties added in quadrature), in various control regions with the inverted $\Delta\phi$ selection applied to enhance the QCD yield.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/supMoriondLdpNJets_HTMHT6.png Figure 9b: Distribution of the multiplicity of jets as observed (points, with statistical uncertainties) and as predicted by applying the data-driven methods of background determination (shaded distributions with statistical and systematic uncertainties added in quadrature), in various control regions with the inverted $\Delta\phi$ selection applied to enhance the QCD yield.
 
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/supMoriondLdpNJets_HTMHT8.png Figure 9c : Distributions of the multiplicity of jets as observed (points, with statistical uncertainties) and as predicted by applying the data-driven methods of background determination (shaded distributions with statistical and systematic uncertainties added in quadrature), in various control regions with the inverted $\Delta\phi$ selection applied to enhance the QCD yield.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/supMoriondLdpBtags_HTMHT3.png Figure 9d : Distributions of the multiplicity of b-tagged jets as observed (points, with statistical uncertainties) and as predicted by applying the data-driven methods of background determination (shaded distributions with statistical and systematic uncertainties added in quadrature), in various control regions with the inverted $\Delta\phi$ selection applied to enhance the QCD yield.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/supMoriondLdpBtags_HTMHT6.png Figure 9e: Distributions of the multiplicity of b-tagged jets as observed (points, with statistical uncertainties) and as predicted by applying the data-driven methods of background determination (shaded distributions with statistical and systematic uncertainties added in quadrature), in various control regions with the inverted $\Delta\phi$ selection applied to enhance the QCD yield.
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Figure Caption
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2D-T1tttt.png Figure 14a : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\rm jet}$ and $N_{\rm b-jet}$, integrated over search regions with $H_{\rm T}^{\rm miss}>750$ GeV and $H_{\rm T}>750$ GeV. An example T1tttt signal scenario with $m_{\tilde{\rm g}}=1500$ GeV and $m_{\tilde{\chi}_1^0}=100$ GeV is shown by the (stacked) purple histogram.
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2D-T1tttt.png Figure 14a : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\rm jet}$ and $N_{\rm b-jet}$, integrated over search regions with $H_{\rm T}^{\rm miss}&amp;gt;750$ GeV and $H_{\rm T}&amp;gt;750$ GeV. An example T1tttt signal scenario with $m_{\tilde{\rm g}}=1500$ GeV and $m_{\tilde{\chi}_1^0}=100$ GeV is shown by the (stacked) purple histogram.
 
2D-T1tttt-pull.png Figure 14b : The same distributions shown in Add. Fig. 14a, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
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2D-T1bbbb.png Figure 14c : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\rm jet}$ and $N_{\rm b-jet}$, integrated over search regions with $H_{\rm T}^{\rm miss}>750$ GeV and $H_{\rm T}>750$ GeV. An example T1bbbb signal scenario with $m_{\tilde{\rm g}}=1500$ GeV and $m_{\tilde{\chi}_1^0}=100$ GeV is shown by the (stacked) purple histogram.
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2D-T1bbbb.png Figure 14c : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\rm jet}$ and $N_{\rm b-jet}$, integrated over search regions with $H_{\rm T}^{\rm miss}&amp;gt;750$ GeV and $H_{\rm T}&amp;gt;750$ GeV. An example T1bbbb signal scenario with $m_{\tilde{\rm g}}=1500$ GeV and $m_{\tilde{\chi}_1^0}=100$ GeV is shown by the (stacked) purple histogram.
 
2D-T1bbbb-pull.png Figure 14d : The same distributions shown in Add. Fig. 14c, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
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2D-T1qqqq.png Figure 14e : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\rm jet}$ and $N_{\rm b-jet}$, integrated over search regions with $H_{\rm T}^{\rm miss}>750$ GeV and $H_{\rm T}>750$ GeV. An example T1qqqq signal scenario with $m_{\tilde{\rm g}}=1400$ GeV and $m_{\tilde{\chi}_1^0}=100$ GeV is shown by the (stacked) purple histogram.
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2D-T1qqqq.png Figure 14e : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\rm jet}$ and $N_{\rm b-jet}$, integrated over search regions with $H_{\rm T}^{\rm miss}&amp;gt;750$ GeV and $H_{\rm T}&amp;gt;750$ GeV. An example T1qqqq signal scenario with $m_{\tilde{\rm g}}=1400$ GeV and $m_{\tilde{\chi}_1^0}=100$ GeV is shown by the (stacked) purple histogram.
 
2D-T1qqqq-pull.png Figure 14f : The same distributions shown in Add. Fig. 14e, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
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2D-T2tt.png Figure 14g : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\rm jet}$ and $N_{\rm b-jet}$, integrated over search regions with $H_{\rm T}^{\rm miss}>750$ GeV and $H_{\rm T}>750$ GeV. An example T2tt signal scenario with $m_{\tilde{\rm t}}=700$ GeV and $m_{\tilde{\chi}_1^0}=50$ GeV is shown by the (stacked) purple histogram.
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2D-T2tt.png Figure 14g : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\rm jet}$ and $N_{\rm b-jet}$, integrated over search regions with $H_{\rm T}^{\rm miss}&amp;gt;750$ GeV and $H_{\rm T}&amp;gt;750$ GeV. An example T2tt signal scenario with $m_{\tilde{\rm t}}=700$ GeV and $m_{\tilde{\chi}_1^0}=50$ GeV is shown by the (stacked) purple histogram.
 
2D-T2tt-pull.png Figure 14h : The same distributions shown in Add. Fig. 14g, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
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2D-T2bb.png Figure 14i : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\rm jet}$ and $N_{\rm b-jet}$, integrated over search regions with $H_{\rm T}^{\rm miss}>750$ GeV and $H_{\rm T}>750$ GeV. An example T2bb signal scenario with $m_{\tilde{\rm b}}=650$ GeV and $m_{\tilde{\chi}_1^0}=1$ GeV is shown by the (stacked) purple histogram.
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2D-T2bb.png Figure 14i : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\rm jet}$ and $N_{\rm b-jet}$, integrated over search regions with $H_{\rm T}^{\rm miss}&amp;gt;750$ GeV and $H_{\rm T}&amp;gt;750$ GeV. An example T2bb signal scenario with $m_{\tilde{\rm b}}=650$ GeV and $m_{\tilde{\chi}_1^0}=1$ GeV is shown by the (stacked) purple histogram.
 
2D-T2bb-pull.png Figure 14j : The same distributions shown in Add. Fig. 14i, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
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2D-T2qq.png Figure 14k : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\rm jet}$ and $N_{\rm b-jet}$, integrated over search regions with $H_{\rm T}^{\rm miss}>750$ GeV and $H_{\rm T}>750$ GeV. An example T2qq signal scenario with $m_{\tilde{\rm b}}=1000$ GeV and $m_{\tilde{\chi}_1^0}=100$ GeV is shown by the (stacked) purple histogram.
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2D-T2qq.png Figure 14k : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\rm jet}$ and $N_{\rm b-jet}$, integrated over search regions with $H_{\rm T}^{\rm miss}&amp;gt;750$ GeV and $H_{\rm T}&amp;gt;750$ GeV. An example T2qq signal scenario with $m_{\tilde{\rm b}}=1000$ GeV and $m_{\tilde{\chi}_1^0}=100$ GeV is shown by the (stacked) purple histogram.
 
2D-T2qq-pull.png Figure 14l : The same distributions shown in Add. Fig. 14k, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.

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Revision 112017-05-03 - KevinPedro

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META TOPICPARENT name="RA2b13TeV"

Search for supersymmetry in multijet events with missing transverse momentum in proton-proton collisions at 13 TeV (SUS-16-033)

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Figure Caption
Changed:
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njets-projection.png Figure 12a : One-dimensional projection of observed number of events and pre-fit background predictions in the search region in $N_{\mathrm jet}$.
njets-projection-pull.png Figure 12b : The same distributions shown in Add. Fig. 12a, with the pull for each bin, defined as $(N_{\mathrm Obs.}-N_{\mathrm Pred.})/\sqrt{N_{\mathrm Pred.}+(\delta N_{\mathrm Pred.})^2}$, shown in the lower panel of the plot.
nbjets-projection.png Figure 12c : One-dimensional projection of observed number of events and pre-fit background predictions in the search region in $N_{\mathrm b-jet}$.
nbjets-projection-pull.png Figure 12d : The same distributions shown in Add. Fig. 12c, with the pull for each bin, defined as $(N_{\mathrm Obs.}-N_{\mathrm Pred.})/\sqrt{N_{\mathrm Pred.}+(\delta N_{\mathrm Pred.})^2}$, shown in the lower panel of the plot.
mht-projection.png Figure 12e : One-dimensional projection of observed number of events and pre-fit background predictions in the search region in $H_{T}^{\mathrm miss}$.
mht-projection-pull.png Figure 12f : The same distributions shown in Add. Fig. 12e, with the pull for each bin, defined as $(N_{\mathrm Obs.}-N_{\mathrm Pred.})/\sqrt{N_{\mathrm Pred.}+(\delta N_{\mathrm Pred.})^2}$, shown in the lower panel of the plot.
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njets-projection.png Figure 12a : One-dimensional projection of observed number of events and pre-fit background predictions in the search region in $N_{\rm jet}$.
njets-projection-pull.png Figure 12b : The same distributions shown in Add. Fig. 12a, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
nbjets-projection.png Figure 12c : One-dimensional projection of observed number of events and pre-fit background predictions in the search region in $N_{\rm b-jet}$.
nbjets-projection-pull.png Figure 12d : The same distributions shown in Add. Fig. 12c, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
mht-projection.png Figure 12e : One-dimensional projection of observed number of events and pre-fit background predictions in the search region in $H_{\rm T}^{\rm miss}$.
mht-projection-pull.png Figure 12f : The same distributions shown in Add. Fig. 12e, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
 
Figure Caption
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T1tttt-projection-pull.png Figure 13a : The same distributions shown in Fig. 11a in the body of the paper, with the pull for each bin, defined as $(N_{\mathrm Obs.}-N_{\mathrm Pred.})/\sqrt{N_{\mathrm Pred.}+(\delta N_{\mathrm Pred.})^2}$, shown in the lower panel of the plot.
T1bbbb-projection-pull.png Figure 13b : The same distributions shown in Fig. 11b in the body of the paper, with the pull for each bin, defined as $(N_{\mathrm Obs.}-N_{\mathrm Pred.})/\sqrt{N_{\mathrm Pred.}+(\delta N_{\mathrm Pred.})^2}$, shown in the lower panel of the plot.
T1qqqq-projection-pull.png Figure 13c : The same distributions shown in Fig. 11c in the body of the paper, with the pull for each bin, defined as $(N_{\mathrm Obs.}-N_{\mathrm Pred.})/\sqrt{N_{\mathrm Pred.}+(\delta N_{\mathrm Pred.})^2}$, shown in the lower panel of the plot.
T2tt-projection-pull.png Figure 13d : The same distributions shown in Fig. 11d in the body of the paper, with the pull for each bin, defined as $(N_{\mathrm Obs.}-N_{\mathrm Pred.})/\sqrt{N_{\mathrm Pred.}+(\delta N_{\mathrm Pred.})^2}$, shown in the lower panel of the plot.
T2bb-projection-pull.png Figure 13e : The same distributions shown in Fig. 11e in the body of the paper, with the pull for each bin, defined as $(N_{\mathrm Obs.}-N_{\mathrm Pred.})/\sqrt{N_{\mathrm Pred.}+(\delta N_{\mathrm Pred.})^2}$, shown in the lower panel of the plot.
T2qq-projection-pull.png Figure 13f : The same distributions shown in Fig. 11f in the body of the paper, with the pull for each bin, defined as $(N_{\mathrm Obs.}-N_{\mathrm Pred.})/\sqrt{N_{\mathrm Pred.}+(\delta N_{\mathrm Pred.})^2}$, shown in the lower panel of the plot.
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T1tttt-projection-pull.png Figure 13a : The same distributions shown in Fig. 11a in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
T1bbbb-projection-pull.png Figure 13b : The same distributions shown in Fig. 11b in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
T1qqqq-projection-pull.png Figure 13c : The same distributions shown in Fig. 11c in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
T2tt-projection-pull.png Figure 13d : The same distributions shown in Fig. 11d in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
T2bb-projection-pull.png Figure 13e : The same distributions shown in Fig. 11e in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
T2qq-projection-pull.png Figure 13f : The same distributions shown in Fig. 11f in the body of the paper, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
 
Figure Caption
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2D-T1tttt.png Figure 14a : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\mathrm jet}$ and $N_{\mathrm b-jet}$, integrated over search regions with $H_{T}^{\mathrm miss}>750$ GeV and $H_{T}>750$ GeV. An example T1tttt signal scenario with $m_{\tilde{g}}=1500$ GeV and $m_{\tilde{\chi}_1^0}=100$ GeV is shown by the (stacked) purple histogram.
2D-T1tttt-pull.png Figure 14b : The same distributions shown in Add. Fig. 14a, with the pull for each bin, defined as $(N_{\mathrm Obs.}-N_{\mathrm Pred.})/\sqrt{N_{\mathrm Pred.}+(\delta N_{\mathrm Pred.})^2}$, shown in the lower panel of the plot.
2D-T1bbbb.png Figure 14c : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\mathrm jet}$ and $N_{\mathrm b-jet}$, integrated over search regions with $H_{T}^{\mathrm miss}>750$ GeV and $H_{T}>750$ GeV. An example T1bbbb signal scenario with $m_{\tilde{g}}=1500$ GeV and $m_{\tilde{\chi}_1^0}=100$ GeV is shown by the (stacked) purple histogram.
2D-T1bbbb-pull.png Figure 14d : The same distributions shown in Add. Fig. 14c, with the pull for each bin, defined as $(N_{\mathrm Obs.}-N_{\mathrm Pred.})/\sqrt{N_{\mathrm Pred.}+(\delta N_{\mathrm Pred.})^2}$, shown in the lower panel of the plot.
2D-T1qqqq.png Figure 14e : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\mathrm jet}$ and $N_{\mathrm b-jet}$, integrated over search regions with $H_{T}^{\mathrm miss}>750$ GeV and $H_{T}>750$ GeV. An example T1qqqq signal scenario with $m_{\tilde{g}}=1400$ GeV and $m_{\tilde{\chi}_1^0}=100$ GeV is shown by the (stacked) purple histogram.
2D-T1qqqq-pull.png Figure 14f : The same distributions shown in Add. Fig. 14e, with the pull for each bin, defined as $(N_{\mathrm Obs.}-N_{\mathrm Pred.})/\sqrt{N_{\mathrm Pred.}+(\delta N_{\mathrm Pred.})^2}$, shown in the lower panel of the plot.
2D-T2tt.png Figure 14g : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\mathrm jet}$ and $N_{\mathrm b-jet}$, integrated over search regions with $H_{T}^{\mathrm miss}>750$ GeV and $H_{T}>750$ GeV. An example T2tt signal scenario with $m_{\tilde{t}}=700$ GeV and $m_{\tilde{\chi}_1^0}=50$ GeV is shown by the (stacked) purple histogram.
2D-T2tt-pull.png Figure 14h : The same distributions shown in Add. Fig. 14g, with the pull for each bin, defined as $(N_{\mathrm Obs.}-N_{\mathrm Pred.})/\sqrt{N_{\mathrm Pred.}+(\delta N_{\mathrm Pred.})^2}$, shown in the lower panel of the plot.
2D-T2bb.png Figure 14i : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\mathrm jet}$ and $N_{\mathrm b-jet}$, integrated over search regions with $H_{T}^{\mathrm miss}>750$ GeV and $H_{T}>750$ GeV. An example T2bb signal scenario with $m_{\tilde{b}}=650$ GeV and $m_{\tilde{\chi}_1^0}=1$ GeV is shown by the (stacked) purple histogram.
2D-T2bb-pull.png Figure 14j : The same distributions shown in Add. Fig. 14i, with the pull for each bin, defined as $(N_{\mathrm Obs.}-N_{\mathrm Pred.})/\sqrt{N_{\mathrm Pred.}+(\delta N_{\mathrm Pred.})^2}$, shown in the lower panel of the plot.
2D-T2qq.png Figure 14k : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\mathrm jet}$ and $N_{\mathrm b-jet}$, integrated over search regions with $H_{T}^{\mathrm miss}>750$ GeV and $H_{T}>750$ GeV. An example T2qq signal scenario with $m_{\tilde{b}}=1000$ GeV and $m_{\tilde{\chi}_1^0}=100$ GeV is shown by the (stacked) purple histogram.
2D-T2qq-pull.png Figure 14l : The same distributions shown in Add. Fig. 14k, with the pull for each bin, defined as $(N_{\mathrm Obs.}-N_{\mathrm Pred.})/\sqrt{N_{\mathrm Pred.}+(\delta N_{\mathrm Pred.})^2}$, shown in the lower panel of the plot.
>
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2D-T1tttt.png Figure 14a : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\rm jet}$ and $N_{\rm b-jet}$, integrated over search regions with $H_{\rm T}^{\rm miss}>750$ GeV and $H_{\rm T}>750$ GeV. An example T1tttt signal scenario with $m_{\tilde{\rm g}}=1500$ GeV and $m_{\tilde{\chi}_1^0}=100$ GeV is shown by the (stacked) purple histogram.
2D-T1tttt-pull.png Figure 14b : The same distributions shown in Add. Fig. 14a, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
2D-T1bbbb.png Figure 14c : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\rm jet}$ and $N_{\rm b-jet}$, integrated over search regions with $H_{\rm T}^{\rm miss}>750$ GeV and $H_{\rm T}>750$ GeV. An example T1bbbb signal scenario with $m_{\tilde{\rm g}}=1500$ GeV and $m_{\tilde{\chi}_1^0}=100$ GeV is shown by the (stacked) purple histogram.
2D-T1bbbb-pull.png Figure 14d : The same distributions shown in Add. Fig. 14c, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
2D-T1qqqq.png Figure 14e : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\rm jet}$ and $N_{\rm b-jet}$, integrated over search regions with $H_{\rm T}^{\rm miss}>750$ GeV and $H_{\rm T}>750$ GeV. An example T1qqqq signal scenario with $m_{\tilde{\rm g}}=1400$ GeV and $m_{\tilde{\chi}_1^0}=100$ GeV is shown by the (stacked) purple histogram.
2D-T1qqqq-pull.png Figure 14f : The same distributions shown in Add. Fig. 14e, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
2D-T2tt.png Figure 14g : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\rm jet}$ and $N_{\rm b-jet}$, integrated over search regions with $H_{\rm T}^{\rm miss}>750$ GeV and $H_{\rm T}>750$ GeV. An example T2tt signal scenario with $m_{\tilde{\rm t}}=700$ GeV and $m_{\tilde{\chi}_1^0}=50$ GeV is shown by the (stacked) purple histogram.
2D-T2tt-pull.png Figure 14h : The same distributions shown in Add. Fig. 14g, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
2D-T2bb.png Figure 14i : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\rm jet}$ and $N_{\rm b-jet}$, integrated over search regions with $H_{\rm T}^{\rm miss}>750$ GeV and $H_{\rm T}>750$ GeV. An example T2bb signal scenario with $m_{\tilde{\rm b}}=650$ GeV and $m_{\tilde{\chi}_1^0}=1$ GeV is shown by the (stacked) purple histogram.
2D-T2bb-pull.png Figure 14j : The same distributions shown in Add. Fig. 14i, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
2D-T2qq.png Figure 14k : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\rm jet}$ and $N_{\rm b-jet}$, integrated over search regions with $H_{\rm T}^{\rm miss}>750$ GeV and $H_{\rm T}>750$ GeV. An example T2qq signal scenario with $m_{\tilde{\rm b}}=1000$ GeV and $m_{\tilde{\chi}_1^0}=100$ GeV is shown by the (stacked) purple histogram.
2D-T2qq-pull.png Figure 14l : The same distributions shown in Add. Fig. 14k, with the pull for each bin, defined as $(N_{\rm Obs.}-N_{\rm Pred.})/\sqrt{N_{\rm Pred.}+(\delta N_{\rm Pred.})^2}$, shown in the lower panel of the plot.
  </>
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Revision 102017-05-02 - AditeePrabhakarRane

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META TOPICPARENT name="RA2b13TeV"

Search for supersymmetry in multijet events with missing transverse momentum in proton-proton collisions at 13 TeV (SUS-16-033)

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Revision 92017-05-02 - JohnBradmillerFeld

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META TOPICPARENT name="RA2b13TeV"

Search for supersymmetry in multijet events with missing transverse momentum in proton-proton collisions at 13 TeV (SUS-16-033)

Line: 80 to 80
 
T1qqqq-projection-pull.png Figure 13c : The same distributions shown in Fig. 11c in the body of the paper, with the pull for each bin, defined as $(N_{\mathrm Obs.}-N_{\mathrm Pred.})/\sqrt{N_{\mathrm Pred.}+(\delta N_{\mathrm Pred.})^2}$, shown in the lower panel of the plot.
T2tt-projection-pull.png Figure 13d : The same distributions shown in Fig. 11d in the body of the paper, with the pull for each bin, defined as $(N_{\mathrm Obs.}-N_{\mathrm Pred.})/\sqrt{N_{\mathrm Pred.}+(\delta N_{\mathrm Pred.})^2}$, shown in the lower panel of the plot.
T2bb-projection-pull.png Figure 13e : The same distributions shown in Fig. 11e in the body of the paper, with the pull for each bin, defined as $(N_{\mathrm Obs.}-N_{\mathrm Pred.})/\sqrt{N_{\mathrm Pred.}+(\delta N_{\mathrm Pred.})^2}$, shown in the lower panel of the plot.
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/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/T2qq-projection-pulll.png Figure 13f : The same distributions shown in Fig. 11f in the body of the paper, with the pull for each bin, defined as $(N_{\mathrm Obs.}-N_{\mathrm Pred.})/\sqrt{N_{\mathrm Pred.}+(\delta N_{\mathrm Pred.})^2}$, shown in the lower panel of the plot.
>
>
T2qq-projection-pull.png Figure 13f : The same distributions shown in Fig. 11f in the body of the paper, with the pull for each bin, defined as $(N_{\mathrm Obs.}-N_{\mathrm Pred.})/\sqrt{N_{\mathrm Pred.}+(\delta N_{\mathrm Pred.})^2}$, shown in the lower panel of the plot.

Figure Caption
2D-T1tttt.png Figure 14a : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\mathrm jet}$ and $N_{\mathrm b-jet}$, integrated over search regions with $H_{T}^{\mathrm miss}>750$ GeV and $H_{T}>750$ GeV. An example T1tttt signal scenario with $m_{\tilde{g}}=1500$ GeV and $m_{\tilde{\chi}_1^0}=100$ GeV is shown by the (stacked) purple histogram.
2D-T1tttt-pull.png Figure 14b : The same distributions shown in Add. Fig. 14a, with the pull for each bin, defined as $(N_{\mathrm Obs.}-N_{\mathrm Pred.})/\sqrt{N_{\mathrm Pred.}+(\delta N_{\mathrm Pred.})^2}$, shown in the lower panel of the plot.
2D-T1bbbb.png Figure 14c : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\mathrm jet}$ and $N_{\mathrm b-jet}$, integrated over search regions with $H_{T}^{\mathrm miss}>750$ GeV and $H_{T}>750$ GeV. An example T1bbbb signal scenario with $m_{\tilde{g}}=1500$ GeV and $m_{\tilde{\chi}_1^0}=100$ GeV is shown by the (stacked) purple histogram.
2D-T1bbbb-pull.png Figure 14d : The same distributions shown in Add. Fig. 14c, with the pull for each bin, defined as $(N_{\mathrm Obs.}-N_{\mathrm Pred.})/\sqrt{N_{\mathrm Pred.}+(\delta N_{\mathrm Pred.})^2}$, shown in the lower panel of the plot.
2D-T1qqqq.png Figure 14e : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\mathrm jet}$ and $N_{\mathrm b-jet}$, integrated over search regions with $H_{T}^{\mathrm miss}>750$ GeV and $H_{T}>750$ GeV. An example T1qqqq signal scenario with $m_{\tilde{g}}=1400$ GeV and $m_{\tilde{\chi}_1^0}=100$ GeV is shown by the (stacked) purple histogram.
2D-T1qqqq-pull.png Figure 14f : The same distributions shown in Add. Fig. 14e, with the pull for each bin, defined as $(N_{\mathrm Obs.}-N_{\mathrm Pred.})/\sqrt{N_{\mathrm Pred.}+(\delta N_{\mathrm Pred.})^2}$, shown in the lower panel of the plot.
2D-T2tt.png Figure 14g : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\mathrm jet}$ and $N_{\mathrm b-jet}$, integrated over search regions with $H_{T}^{\mathrm miss}>750$ GeV and $H_{T}>750$ GeV. An example T2tt signal scenario with $m_{\tilde{t}}=700$ GeV and $m_{\tilde{\chi}_1^0}=50$ GeV is shown by the (stacked) purple histogram.
2D-T2tt-pull.png Figure 14h : The same distributions shown in Add. Fig. 14g, with the pull for each bin, defined as $(N_{\mathrm Obs.}-N_{\mathrm Pred.})/\sqrt{N_{\mathrm Pred.}+(\delta N_{\mathrm Pred.})^2}$, shown in the lower panel of the plot.
2D-T2bb.png Figure 14i : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\mathrm jet}$ and $N_{\mathrm b-jet}$, integrated over search regions with $H_{T}^{\mathrm miss}>750$ GeV and $H_{T}>750$ GeV. An example T2bb signal scenario with $m_{\tilde{b}}=650$ GeV and $m_{\tilde{\chi}_1^0}=1$ GeV is shown by the (stacked) purple histogram.
2D-T2bb-pull.png Figure 14j : The same distributions shown in Add. Fig. 14i, with the pull for each bin, defined as $(N_{\mathrm Obs.}-N_{\mathrm Pred.})/\sqrt{N_{\mathrm Pred.}+(\delta N_{\mathrm Pred.})^2}$, shown in the lower panel of the plot.
2D-T2qq.png Figure 14k : Observed numbers of events and corresponding SM background predictions in intervals of $N_{\mathrm jet}$ and $N_{\mathrm b-jet}$, integrated over search regions with $H_{T}^{\mathrm miss}>750$ GeV and $H_{T}>750$ GeV. An example T2qq signal scenario with $m_{\tilde{b}}=1000$ GeV and $m_{\tilde{\chi}_1^0}=100$ GeV is shown by the (stacked) purple histogram.
2D-T2qq-pull.png Figure 14l : The same distributions shown in Add. Fig. 14k, with the pull for each bin, defined as $(N_{\mathrm Obs.}-N_{\mathrm Pred.})/\sqrt{N_{\mathrm Pred.}+(\delta N_{\mathrm Pred.})^2}$, shown in the lower panel of the plot.
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Revision 82017-05-01 - JohnBradmillerFeld

Line: 1 to 1
 
META TOPICPARENT name="RA2b13TeV"

Search for supersymmetry in multijet events with missing transverse momentum in proton-proton collisions at 13 TeV (SUS-16-033)

Line: 65 to 66
 
Figure Caption
njets-projection.png Figure 12a : One-dimensional projection of observed number of events and pre-fit background predictions in the search region in $N_{\mathrm jet}$.
Changed:
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njets-projection-pull.png Figure 12b : The same distribution shown in Add. Fig. 12a, with the pull for each bin, defined as $(N_{\mathrm Obs.}-N_{\mathrm Pred.})/\sqrt{N_{\mathrm Pred.}+(\delta N_{\mathrm Pred.})^2}$, shown in the lower panel of each plot.
>
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njets-projection-pull.png Figure 12b : The same distributions shown in Add. Fig. 12a, with the pull for each bin, defined as $(N_{\mathrm Obs.}-N_{\mathrm Pred.})/\sqrt{N_{\mathrm Pred.}+(\delta N_{\mathrm Pred.})^2}$, shown in the lower panel of the plot.
 
nbjets-projection.png Figure 12c : One-dimensional projection of observed number of events and pre-fit background predictions in the search region in $N_{\mathrm b-jet}$.
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nbjets-projection-pull.png Figure 12d : The same distribution shown in Add. Fig. 12c, with the pull for each bin, defined as $(N_{\mathrm Obs.}-N_{\mathrm Pred.})/\sqrt{N_{\mathrm Pred.}+(\delta N_{\mathrm Pred.})^2}$, shown in the lower panel of each plot.
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nbjets-projection-pull.png Figure 12d : The same distributions shown in Add. Fig. 12c, with the pull for each bin, defined as $(N_{\mathrm Obs.}-N_{\mathrm Pred.})/\sqrt{N_{\mathrm Pred.}+(\delta N_{\mathrm Pred.})^2}$, shown in the lower panel of the plot.
 
mht-projection.png Figure 12e : One-dimensional projection of observed number of events and pre-fit background predictions in the search region in $H_{T}^{\mathrm miss}$.
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mht-projection-pull.png Figure 12f : The same distribution shown in Add. Fig. 12e, with the pull for each bin, defined as $(N_{\mathrm Obs.}-N_{\mathrm Pred.})/\sqrt{N_{\mathrm Pred.}+(\delta N_{\mathrm Pred.})^2}$, shown in the lower panel of each plot.
>
>
mht-projection-pull.png Figure 12f : The same distributions shown in Add. Fig. 12e, with the pull for each bin, defined as $(N_{\mathrm Obs.}-N_{\mathrm Pred.})/\sqrt{N_{\mathrm Pred.}+(\delta N_{\mathrm Pred.})^2}$, shown in the lower panel of the plot.

Figure Caption
T1tttt-projection-pull.png Figure 13a : The same distributions shown in Fig. 11a in the body of the paper, with the pull for each bin, defined as $(N_{\mathrm Obs.}-N_{\mathrm Pred.})/\sqrt{N_{\mathrm Pred.}+(\delta N_{\mathrm Pred.})^2}$, shown in the lower panel of the plot.
T1bbbb-projection-pull.png Figure 13b : The same distributions shown in Fig. 11b in the body of the paper, with the pull for each bin, defined as $(N_{\mathrm Obs.}-N_{\mathrm Pred.})/\sqrt{N_{\mathrm Pred.}+(\delta N_{\mathrm Pred.})^2}$, shown in the lower panel of the plot.
T1qqqq-projection-pull.png Figure 13c : The same distributions shown in Fig. 11c in the body of the paper, with the pull for each bin, defined as $(N_{\mathrm Obs.}-N_{\mathrm Pred.})/\sqrt{N_{\mathrm Pred.}+(\delta N_{\mathrm Pred.})^2}$, shown in the lower panel of the plot.
T2tt-projection-pull.png Figure 13d : The same distributions shown in Fig. 11d in the body of the paper, with the pull for each bin, defined as $(N_{\mathrm Obs.}-N_{\mathrm Pred.})/\sqrt{N_{\mathrm Pred.}+(\delta N_{\mathrm Pred.})^2}$, shown in the lower panel of the plot.
T2bb-projection-pull.png Figure 13e : The same distributions shown in Fig. 11e in the body of the paper, with the pull for each bin, defined as $(N_{\mathrm Obs.}-N_{\mathrm Pred.})/\sqrt{N_{\mathrm Pred.}+(\delta N_{\mathrm Pred.})^2}$, shown in the lower panel of the plot.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/T2qq-projection-pulll.png Figure 13f : The same distributions shown in Fig. 11f in the body of the paper, with the pull for each bin, defined as $(N_{\mathrm Obs.}-N_{\mathrm Pred.})/\sqrt{N_{\mathrm Pred.}+(\delta N_{\mathrm Pred.})^2}$, shown in the lower panel of the plot.
 </>
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Line: 115 to 127
 
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Revision 72017-05-01 - JohnBradmillerFeld

Line: 1 to 1
 
META TOPICPARENT name="RA2b13TeV"

Search for supersymmetry in multijet events with missing transverse momentum in proton-proton collisions at 13 TeV (SUS-16-033)

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Revision 62017-04-30 - JohnBradmillerFeld

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META TOPICPARENT name="RA2b13TeV"

Search for supersymmetry in multijet events with missing transverse momentum in proton-proton collisions at 13 TeV (SUS-16-033)

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Figure Caption
t1-signal-q-plot-174-bins.png Figure 11e : The sensitivity of the analysis to different direct gluino production signal models as a function of the analysis binning. The upper panel shows the total predicted SM backgrounds and the expected number of signal events in 35.9 ${\rm fb}^{-1}$ of data for six representative model points per analysis bin. The bottom panel shows the expected sensitivity, expressed in terms of the figure of merit Q, per analysis bin.
t2-signal-q-plot-174-bins.png Figure 11e : The sensitivity of the analysis to different direct squark production signal models as a function of the analysis binning. The upper panel shows the total predicted SM backgrounds and the expected number of signal events in 35.9 ${\rm fb}^{-1}$ of data for six representative model points per analysis bin. The bottom panel shows the expected sensitivity, expressed in terms of the figure of merit Q, per analysis bin.
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Figure Caption
njets-projection.png Figure 12a : One-dimensional projection of observed number of events and pre-fit background predictions in the search region in $N_{\mathrm jet}$.
njets-projection-pull.png Figure 12b : The same distribution shown in Add. Fig. 12a, with the pull for each bin, defined as $(N_{\mathrm Obs.}-N_{\mathrm Pred.})/\sqrt{N_{\mathrm Pred.}+(\delta N_{\mathrm Pred.})^2}$, shown in the lower panel of each plot.
nbjets-projection.png Figure 12c : One-dimensional projection of observed number of events and pre-fit background predictions in the search region in $N_{\mathrm b-jet}$.
nbjets-projection-pull.png Figure 12d : The same distribution shown in Add. Fig. 12c, with the pull for each bin, defined as $(N_{\mathrm Obs.}-N_{\mathrm Pred.})/\sqrt{N_{\mathrm Pred.}+(\delta N_{\mathrm Pred.})^2}$, shown in the lower panel of each plot.
mht-projection.png Figure 12e : One-dimensional projection of observed number of events and pre-fit background predictions in the search region in $H_{T}^{\mathrm miss}$.
mht-projection-pull.png Figure 12f : The same distribution shown in Add. Fig. 12e, with the pull for each bin, defined as $(N_{\mathrm Obs.}-N_{\mathrm Pred.})/\sqrt{N_{\mathrm Pred.}+(\delta N_{\mathrm Pred.})^2}$, shown in the lower panel of each plot.
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Revision 52017-04-30 - SimonThomasKurz

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META TOPICPARENT name="RA2b13TeV"

Search for supersymmetry in multijet events with missing transverse momentum in proton-proton collisions at 13 TeV (SUS-16-033)

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Figure Caption
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MC_BG_Pie_vs_NJets_NBJets.png Figure 1a : Background composition in zero-lepton search region (inclusive in $H_{\rm T}^{\rm miss}$ and $H_{\rm T}$) in bins of the number of jets and the number of b-tagged jets. The expected contribution from each process is obtained from simulation after applying the full baseline selection.
MC_BG_Pie_vs_NJets_NBJets_MHT0.png Figure 1b : Background composition in zero-lepton search region in bins of the number of jets and the number of b-tagged jets for simulated events with $300<H_{\rm T}^{\rm miss}<350$ GeV and $H_{\rm T}>300$ GeV.
MC_BG_Pie_vs_NJets_NBJets_MHT1.png Figure 1c : Background composition in zero-lepton search region in bins of the number of jets and the number of b-tagged jets for simulated events with $350<H_{\rm T}^{\rm miss}<500$ GeV and $H_{\rm T}>350$ GeV.
MC_BG_Pie_vs_NJets_NBJets_MHT2.png Figure 1d : Background composition in zero-lepton search region in bins of the number of jets and the number of b-tagged jets for simulated events with $500<H_{\rm T}^{\rm miss}<750$ GeV and $H_{\rm T}>500$ GeV.
MC_BG_Pie_vs_NJets_NBJets_MHT3.png Figure 1e : Background composition in zero-lepton search region in bins of the number of jets and the number of b-tagged jets for simulated events with $H_{\rm T}^{\rm miss}>750$ GeV and $H_{\rm T}>750$ GeV.
ExpVsPre_HT_baseline_Plot.png Figure 2a : The lost-lepton background as a function of $H_{\rm T}$ of the analysis as determined directly from ttbar, single top quark, W+jets, diboson, and rare-event simulation (points, with statistical uncertainties) and as predicted by applying the lost-lepton background determination procedure to simulated electron and muon control samples (histograms, with statistical uncertainties). The results in the lower panel are obtained through bin-by-bin division of the results in the upper panel, including the uncertainties, by the central values of the "predicted'" results.
ExpVsPre_MHT_baseline_Plot.png Figure 2b : The lost-lepton background as a function of $H_{\rm T}^{\rm miss}$ of the analysis as determined directly from ttbar, single top quark, W+jets, diboson, and rare-event simulation (points, with statistical uncertainties) and as predicted by applying the lost-lepton background determination procedure to simulated electron and muon control samples (histograms, with statistical uncertainties). The results in the lower panel are obtained through bin-by-bin division of the results in the upper panel, including the uncertainties, by the central values of the "predicted" results.
ExpVsPre_NJets_baseline_Plot.png Figure 2c : The lost-lepton background as a function of the number of jets of the analysis as determined directly from ttbar, single top quark, W+jets, diboson, and rare-event simulation (points, with statistical uncertainties) and as predicted by applying the lost-lepton background determination procedure to simulated electron and muon control samples (histograms, with statistical uncertainties). The results in the lower panel are obtained through bin-by-bin division of the results in the upper panel, including the uncertainties, by the central values of the "predicted" results.
ExpVsPre_NBtag_baseline_Plot.png Figure 2d: The lost-lepton background as a function of the number of b-tagged jets of the analysis as determined directly from ttbar, single top quark, W+jets, diboson, and rare-event simulation (points, with statistical uncertainties) and as predicted by applying the lost-lepton background determination procedure to simulated electron and muon control samples (histograms, with statistical uncertainties). The results in the lower panel are obtained through bin-by-bin division of the results in the upper panel, including the uncertainties, by the central values of the "predicted" results.
ExpVsCS_HT_baseline_Plot.png Figure 3a : Comparison of the number of expected lost-lepton background events in the zero (selected) lepton search region (points, with statistical uncertainties) and the sum of single electron and muon control sample events (histograms, with statistical uncertainties) as a function of $H_{\rm T}$ The simulation includes ttbar, single top quark, W+jets, diboson, and rare-event simulation.}
ExpVsCS_MHT_baseline_Plot.png Figure 3b : Comparison of the number of expected lost-lepton background events in the zero (selected) lepton search region (points, with statistical uncertainties) and the sum of single electron and muon control sample events (histograms, with statistical uncertainties) as a function of $H_{\rm T}^{\rm miss}$. The simulation includes ttbar, single top quark, W+jets, diboson, and rare-event simulation.}
ExpVsCS_NJets_baseline_Plot.png Figure 3c : Comparison of the number of expected lost-lepton background events in the zero (selected) lepton search region (points, with statistical uncertainties) and the sum of single electron and muon control sample events (histograms, with statistical uncertainties) as a function of the number of jets. The simulation includes ttbar, single top quark, W+jets, diboson, and rare-event simulation.}
ExpVsCS_NBtag_baseline_Plot.png Figure 3d : Comparison of the number of expected lost-lepton background events in the zero (selected) lepton search region (points, with statistical uncertainties) and the sum of single electron and muon control sample events (histograms, with statistical uncertainties) as a function of the number of b-tagged jets. The simulation includes ttbar, single top quark, W+jets, diboson, and rare-event simulation.}
ExpVsCS_search_baseline_Plot.png Figure 4 : Comparison of the number of expected lost-lepton background events in the zero (selected) lepton search region (points, with statistical uncertainties) and the sum of single electron and muon control sample events (histograms, with statistical uncertainties) as a function of the search region bin number. The simulation includes ttbar, single top quark, W+jets, diboson, and rare-event simulation.
Plot_WgunTemplate.png Figure 5 : The hadronically-decaying $\tau$ lepton ($\tau_{\rm h}$) response templates: distributions of the ratio of $\tau_{\rm h}$ visible-$p_{\rm T}$ to true-$p_{\rm T}$, $p_{\rm T}(\tau_{\rm h}^{\rm visible})/p_{\rm T}(\tau_{\rm h}^{\rm gen})$, in intervals of $p_{\rm T}(\tau_{\rm h}^{\rm gen})$ as determined from a simulation of single ${\rm W}\rightarrow\tau_{\rm h}\nu_{\tau}$ decay events.
PClosure_HT_delphi_stacked_ARElog116_ARElog115_Plot_kRed-9.png Figure 6a : Distributions of $H_{\rm T}$ in background events with a hadronically decaying $\tau$ lepton as predicted directly from simulation (points, with statistical uncertainties) and as predicted by applying the hadronically decaying $\tau$ lepton background determination procedure to simulated muon control sample (shaded regions), for the baseline selection. The simulation includes ttbar, W+jets, and single top quark process events.
PClosure_MHT_delphi_stacked_ARElog116_ARElog115_Plot_kRed-9.png Figure 6b : Distributions of $H_{\rm T}^{\rm miss}$ in background events with a hadronically decaying $\tau$ lepton as predicted directly from simulation (points, with statistical uncertainties) and as predicted by applying the hadronically decaying $\tau$ lepton background determination procedure to simulated muon control sample (shaded regions), for the baseline selection. The simulation includes ttbar, W+jets, and single top quark process events.
PClosure_NJet_delphi_stacked_ARElog116_ARElog115_Plot_kRed-9.png Figure 6c : Distributions of the number of jets in background events with a hadronically decaying $\tau$ lepton as predicted directly from simulation (points, with statistical uncertainties) and as predicted by applying the hadronically decaying $\tau$ lepton background determination procedure to simulated muon control sample (shaded regions), for the baseline selection. The simulation includes ttbar, W+jets, and single top quark process events.
PClosure_NBtag_delphi_stacked_ARElog116_ARElog115_Plot_kRed-9.png Figure 6d : Distributions of the number of b-tagged jets in background events with a hadronically decaying $\tau$ lepton as predicted directly from simulation (points, with statistical uncertainties) and as predicted by applying the hadronically decaying $\tau$ lepton background determination procedure to simulated muon control sample (shaded regions), for the baseline selection. The simulation includes ttbar, W+jets, and single top quark process events.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/rands-closure-ht.png Figure 7a : Distributions of $H_{\rm T}$ in background events with a hadronically decaying $\tau$ lepton as predicted directly from simulation (points, with statistical uncertainties) and as predicted by applying the hadronically decaying $\tau$ lepton background determination procedure to simulated muon control sample (shaded regions), for the baseline selection. The simulation includes ttbar, W+jets, and single top quark process events.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/rands-closure-mht.png Figure 7b : Distributions of $H_{\rm T}^{\rm miss}$ in background events with a hadronically decaying $\tau$ lepton as predicted directly from simulation (points, with statistical uncertainties) and as predicted by applying the hadronically decaying $\tau$ lepton background determination procedure to simulated muon control sample (shaded regions), for the baseline selection. The simulation includes ttbar, W+jets, and single top quark process events.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/rands-closure-njets.png Figure 7c : Distributions of the number of jets in background events with a hadronically decaying $\tau$ lepton as predicted directly from simulation (points, with statistical uncertainties) and as predicted by applying the hadronically decaying $\tau$ lepton background determination procedure to simulated muon control sample (shaded regions), for the baseline selection. The simulation includes ttbar, W+jets, and single top quark process events.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/rands-closure-btags.png Figure 7d : Distributions of the number of b-tagged jets in background events with a hadronically decaying $\tau$ lepton as predicted directly from simulation (points, with statistical uncertainties) and as predicted by applying the hadronically decaying $\tau$ lepton background determination procedure to simulated muon control sample (shaded regions), for the baseline selection. The simulation includes ttbar, W+jets, and single top quark process events.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/rands-closure-dphi1.png Figure 8a : Distributions of the azimuthal separation between the $H_{\rm T}^{\rm miss}$ and the first jet in QCD background events as predicted directly from simulation (points, with statistical uncertainties) and as predicted by applying the rebalance and smear background determination procedure to a simulated QCD sample (shaded distributions with statistical and systematic uncertainties added in quadrature), for a QCD-enhanced modified baseline selection.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/rands-closure-dphi2.png Figure 8b : Distributions of the azimuthal separation between the $H_{\rm T}^{\rm miss}$ and the second jet in QCD background events as predicted directly from simulation (points, with statistical uncertainties) and as predicted by applying the rebalance and smear background determination procedure to a simulated QCD sample (shaded distributions with statistical and systematic uncertainties added in quadrature), for a QCD-enhanced modified baseline selection.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/rands-closure-dphi3.png Figure 8c : Distributions of the azimuthal separation between the $H_{\rm T}^{\rm miss}$ and the third jet in QCD background events as predicted directly from simulation (points, with statistical uncertainties) and as predicted by applying the rebalance and smear background determination procedure to a simulated QCD sample (shaded distributions with statistical and systematic uncertainties added in quadrature), for a QCD-enhanced modified baseline selection.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/rands-closure-dphi4.png Figure 8d : Distributions of the azimuthal separation between the $H_{\rm T}^{\rm miss}$ and the fourth jet in QCD background events as predicted directly from simulation (points, with statistical uncertainties) and as predicted by applying the rebalance and smear background determination procedure to a simulated QCD sample (shaded distributions with statistical and systematic uncertainties added in quadrature), for a QCD-enhanced modified baseline selection.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/supMoriondLdpNJets_HTMHT3.png Figure 9a : Distributions of the multiplicity of jets as observed (points, with statistical uncertainties) and as predicted by applying the data-driven methods of background determination (shaded distributions with statistical and systematic uncertainties added in quadrature), in various control regions with the inverted $\Delta\phi$ selection applied to enhance the QCD yield.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/supMoriondLdpNJets_HTMHT6.png Figure 9b: Distributions of the multiplicity of jets as observed (points, with statistical uncertainties) and as predicted by applying the data-driven methods of background determination (shaded distributions with statistical and systematic uncertainties added in quadrature), in various control regions with the inverted $\Delta\phi$ selection applied to enhance the QCD yield.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/supMoriondLdpNJets_HTMHT8.png Figure 9c : Distributions of the multiplicity of jets as observed (points, with statistical uncertainties) and as predicted by applying the data-driven methods of background determination (shaded distributions with statistical and systematic uncertainties added in quadrature), in various control regions with the inverted $\Delta\phi$ selection applied to enhance the QCD yield.
/twiki/pub/CMSPublic/PhysicsResultsSUS16033-PAPER/supMoriondLdpBtags_HTMHT3.png Figure 9d : Distributions of the multiplicity of b-tagged jets as observed (points, with statistical uncertainties) and as predicted by applying the data-driven methods of background determination (shaded distributions with statistical and systematic uncertainties added in quadrature), in various control regions with the inverted $\Delta\phi$ selection applied to enhance the QCD yield.