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| CMS-SUS-19-006 ; CERN-EP-2019-152 | ||
| Search for supersymmetry in proton-proton collisions at 13 TeV in final states with jets and missing transverse momentum | ||
| CMS Collaboration | ||
| 13 August 2019 | ||
| JHEP 10 (2019) 244 | ||
| Abstract: Results are reported from a search for supersymmetric particles in the final state with multiple jets and large missing transverse momentum. The search uses a sample of proton-proton collisions at $\sqrt{s} = $ 13 TeV collected with the CMS detector in 2016-2018, corresponding to an integrated luminosity of 137 fb$^{-1}$, representing essentially the full LHC Run 2 data sample. The analysis is performed in a four-dimensional search region defined in terms of the number of jets, the number of tagged bottom quark jets, the scalar sum of jet transverse momenta, and the magnitude of the vector sum of jet transverse momenta. No significant excess in the event yield is observed relative to the expected background contributions from standard model processes. Limits on the pair production of gluinos and squarks are obtained in the framework of simplified models for supersymmetric particle production and decay processes. Assuming the lightest supersymmetric particle to be a neutralino, lower limits on the gluino mass as large as 2000 to 2310 GeV are obtained at 95% confidence level, while lower limits on the squark mass as large as 1190 to 1630 GeV are obtained, depending on the production scenario. | ||
| Links: e-print arXiv:1908.04722 [hep-ex] (PDF) ; CDS record ; inSPIRE record ; HepData record ; CADI line (restricted) ; | ||
| Figures & Tables | Summary | Additional Figures & Tables | References | CMS Publications |
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| Figures | |
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Figure 1:
Diagrams for the simplified models with direct gluino pair production considered in this study: (upper left) T1tttt, (upper right) T1bbbb, (lower left) T1qqqq, and (lower right) T5qqqqVV. |
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Figure 1-a:
Diagram for the T1tttt simplified model of direct gluino pair production. |
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Figure 1-b:
Diagram for the T1bbbb simplified model of direct gluino pair production. |
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Figure 1-c:
Diagram for the T1qqqq simplified model of direct gluino pair production. |
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Figure 1-d:
Diagram for the T5qqqqVV simplified model of direct gluino pair production. |
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Figure 2:
Diagrams for the simplified models with direct squark pair production considered in this study: (left) T2tt, (middle) T2bb, and (right) T2qq. |
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Figure 2-a:
Diagram for the T2tt simplified model of direct squark pair production. |
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Figure 2-b:
Diagram for the T2bb simplified model of direct squark pair production. |
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Figure 2-c:
Diagram for the T2qq simplified model of direct squark pair production. |
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Figure 3:
Schematic illustration of the 10 kinematic search intervals in the ${H_{\mathrm {T}}^{\text {miss}}}$ versus ${H_{\mathrm {T}}}$ plane. The region above the red dashed line, with $ {H_{\mathrm {T}}^{\text {miss}}} > {H_{\mathrm {T}}} $, is excluded, as are all of regions 1 and 4 for $ {N_{\text {jet}}} \geq $ 8. The rightmost and topmost bins are unbounded, extending to $ {H_{\mathrm {T}}} =\infty $ and $ {H_{\mathrm {T}}^{\text {miss}}} =\infty $, respectively. |
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Figure 4:
(upper) The number of lost-lepton events in simulation, integrated over ${H_{\mathrm {T}}}$ and ${H_{\mathrm {T}}^{\text {miss}}}$, as a function of ${N_{\text {jet}}}$ and ${N_{{\mathrm{b}}\text {-jet}}}$. (middle) Corresponding results from simulation for the number of events in the single-lepton control region. (lower) The ratio of the simulated lost-lepton to the single-lepton results, with statistical uncertainties (too small to be visible). These ratios are equivalent to the transfer factors used in the evaluation of the lost-lepton background, except integrated over ${H_{\mathrm {T}}}$ and ${H_{\mathrm {T}}^{\text {miss}}}$. |
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Figure 5:
The (upper) number of events in the ${\gamma}$+jets control region for data and simulation and (lower) transfer factors ${\mathcal {R}_{{\mathrm{Z} \to \nu \bar{\nu}} /\gamma}^{\text {sim}}}$ from simulation. The respective results are shown for the 46 search bins with $ {N_{{\mathrm{b}}\text {-jet}}} =$ 0. The 10 results (8 for $ {N_{\text {jet}}} \geq $ 8) within each region delineated by vertical dashed lines correspond sequentially to the 10 (8) kinematic intervals in ${H_{\mathrm {T}}}$ and ${H_{\mathrm {T}}^{\text {miss}}}$ listed in Table 1 and Fig. 3. The uncertainties are statistical only. For the upper plot, the simulated results show the stacked event rates for the ${\gamma}$+jets and nonprompt MC event samples, where "nonprompt'' refers to SM MC events other than ${\gamma}$+jets. The simulated nonprompt results are dominated by events from the QCD sample. Because of limited statistical precision in the simulated event samples at large ${N_{\text {jet}}}$, the transfer factors determined for the 8 $\leq {N_{\text {jet}}} \leq $ 9 region are also used for the $ {N_{\text {jet}}} > $ 10 region. |
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Figure 6:
(upper) The observed event yield in the ${\mathrm{Z} (\to \ell ^{+}\ell ^{-})}$+jets control region, integrated over ${H_{\mathrm {T}}}$ and ${H_{\mathrm {T}}^{\text {miss}}}$, as a function of ${N_{\text {jet}}}$ and ${N_{{\mathrm{b}}\text {-jet}}}$. The uncertainties are statistical only. The stacked histograms show the corresponding results from simulation. (lower) The extrapolation factors ${\mathcal {F}_{\mathrm {j},\mathrm{b}}^{\text {data}}}$ with their statistical uncertainties. |
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Figure 7:
Prediction from simulation for the ${\mathrm{Z} (\to \ell ^{+}\ell ^{-})}$+jets event yields in the 174 search bins as determined by computing the ${\mathcal {F}_{\mathrm {j},\mathrm{b}}^{\text {data}}}$ factors (Eq. (3)) and the $ {N_{{\mathrm{b}}\text {-jet}}} =$ 0 event yields in the same manner as for data, in comparison to the corresponding direct ${\mathrm{Z} (\to \ell ^{+}\ell ^{-})}$+jets prediction from simulation. The 10 results (8 for $ {N_{\text {jet}}} \geq $ 8) within each region delineated by vertical dashed lines correspond sequentially to the 10 (8) kinematic intervals in ${H_{\mathrm {T}}}$ and ${H_{\mathrm {T}}^{\text {miss}}}$ listed in Table 1 and Fig. 3. For bins with $ {N_{\text {jet}}} \geq $ 10, some points do not appear in the upper panel because they lie below the minimum of the displayed range. In the case that the direct expected yield is zero, there is no result in the lower, ratio panel. The pink bands show the statistical uncertainties in the prediction, scaled to correspond to the integrated luminosity of the data, combined with the systematic uncertainty attributable to the kinematic (${H_{\mathrm {T}}}$ and ${H_{\mathrm {T}}^{\text {miss}}}$) dependence. The black error bars show the statistical uncertainties in the simulation. For bins corresponding to $ {N_{{\mathrm{b}}\text {-jet}}} = $ 0, the agreement is exact by construction. |
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Figure 8:
The observed and predicted distributions of (left) ${H_{\mathrm {T}}^{\text {miss}}}$ in the inverted-$ {\Delta \phi}$ control region and (right) ${H_{\mathrm {T}}}$ in the low-${H_{\mathrm {T}}^{\text {miss}}}$ sideband. The uncertainties are statistical only. The lower panels show the ratios of the observed to the predicted distributions, with their statistical uncertainties. The hatched regions indicate the total uncertainties in the predictions, with statistical and systematic uncertainties combined in quadrature. |
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Figure 8-a:
The observed and predicted distributions of ${H_{\mathrm {T}}^{\text {miss}}}$ in the inverted-$ {\Delta \phi}$ control region. The uncertainties are statistical only. The lower panel shows the ratio of the observed to the predicted distributions, with their statistical uncertainties. The hatched regions indicate the total uncertainties in the predictions, with statistical and systematic uncertainties combined in quadrature. |
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Figure 8-b:
The observed and predicted distributions of ${H_{\mathrm {T}}}$ in the low-${H_{\mathrm {T}}^{\text {miss}}}$ sideband. The uncertainties are statistical only. The lower panel shows the ratio of the observed to the predicted distributions, with their statistical uncertainties. The hatched regions indicate the total uncertainties in the predictions, with statistical and systematic uncertainties combined in quadrature. |
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Figure 9:
Distribution of observed and predicted event yields in the inverted-$ {\Delta \phi}$ control region analysis bins. The uncertainties are statistical only. The labeling of the bin numbers is the same as in Fig. 7. The lower panel shows the ratio of the observed to the predicted event yields, with their statistical uncertainties. The hatched region indicates the total uncertainty in the prediction, with statistical and systematic uncertainties combined in quadrature. |
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Figure 10:
The observed numbers of events and pre-fit SM background predictions in the 174 search bins of the analysis, where "pre-fit'' means there is no constraint from the likelihood fit. The labeling of the bin numbers is the same as in Fig. 7. Numerical values are given in Appendix A. The hatching indicates the total uncertainty in the background predictions. The lower panel displays the fractional differences between the data and SM predictions. |
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Figure 11:
One-dimensional projections of the data and pre-fit SM predictions in ${H_{\mathrm {T}}^{\text {miss}}}$, ${N_{\text {jet}}}$, and ${N_{{\mathrm{b}}\text {-jet}}}$. The hatched regions indicate the total uncertainties in the background predictions. The (unstacked) results for two example signal scenarios are shown in each instance, one with $ {\Delta m} \gg $ 0 and the other with $ {\Delta m} \approx $ 0, where ${\Delta m}$ is the difference between the gluino or squark mass and the sum of the masses of the particles into which it decays. |
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Figure 11-a:
One-dimensional projection of the data and pre-fit SM predictions in ${H_{\mathrm {T}}^{\text {miss}}}$. The hatched regions indicate the total uncertainties in the background predictions. The (unstacked) results for two example signal scenarios are shown in each instance, one with $ {\Delta m} \gg $ 0 and the other with $ {\Delta m} \approx $ 0, where ${\Delta m}$ is the difference between the gluino or squark mass and the sum of the masses of the particles into which it decays. |
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Figure 11-b:
One-dimensional projection of the data and pre-fit SM predictions in ${N_{\text {jet}}}$. The hatched regions indicate the total uncertainties in the background predictions. The (unstacked) results for two example signal scenarios are shown in each instance, one with $ {\Delta m} \gg $ 0 and the other with $ {\Delta m} \approx $ 0, where ${\Delta m}$ is the difference between the gluino or squark mass and the sum of the masses of the particles into which it decays. |
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Figure 11-c:
One-dimensional projection of the data and pre-fit SM predictions in ${N_{{\mathrm{b}}\text {-jet}}}$. The hatched regions indicate the total uncertainties in the background predictions. The (unstacked) results for two example signal scenarios are shown in each instance, one with $ {\Delta m} \gg $ 0 and the other with $ {\Delta m} \approx $ 0, where ${\Delta m}$ is the difference between the gluino or squark mass and the sum of the masses of the particles into which it decays. |
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Figure 12:
One-dimensional projections of the data and pre-fit SM predictions in either ${H_{\mathrm {T}}^{\text {miss}}}$, ${N_{\text {jet}}}$, or ${N_{{\mathrm{b}}\text {-jet}}}$ after applying additional selection criteria, given in the figure legends, to enhance the sensitivity to the (upper left) T1tttt, (upper right) T1bbbb, (middle left) T1qqqq, (middle right) T2tt, (lower left) T2bb, and (lower right) T2qq signal processes. The (unstacked) results for two example signal scenarios are shown in each instance, one with $ {\Delta m} \gg $ 0 and the other with $ {\Delta m} \approx $ 0, where ${\Delta m}$ is the difference between the gluino or squark mass and the sum of the masses of the particles into which it decays. |
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Figure 12-a:
One-dimensional projections of the data and pre-fit SM predictions in ${N_{\text {jet}}}$ after applying additional selection criteria, given in the figure legends, to enhance the sensitivity to the T1tttt signal process. The (unstacked) results for two example signal scenarios are shown, one with $ {\Delta m} \gg $ 0 and the other with $ {\Delta m} \approx $ 0, where ${\Delta m}$ is the difference between the gluino or squark mass and the sum of the masses of the particles into which it decays. |
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Figure 12-b:
One-dimensional projections of the data and pre-fit SM predictions in ${N_{{\mathrm{b}}\text {-jet}}}$ after applying additional selection criteria, given in the figure legends, to enhance the sensitivity to the T1bbbb signal process. The (unstacked) results for two example signal scenarios are shown, one with $ {\Delta m} \gg $ 0 and the other with $ {\Delta m} \approx $ 0, where ${\Delta m}$ is the difference between the gluino or squark mass and the sum of the masses of the particles into which it decays. |
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Figure 12-c:
One-dimensional projections of the data and pre-fit SM predictions in ${H_{\mathrm {T}}^{\text {miss}}}$ after applying additional selection criteria, given in the figure legends, to enhance the sensitivity to the T1qqqq signal process. The (unstacked) results for two example signal scenarios are shown, one with $ {\Delta m} \gg $ 0 and the other with $ {\Delta m} \approx $ 0, where ${\Delta m}$ is the difference between the gluino or squark mass and the sum of the masses of the particles into which it decays. |
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Figure 12-d:
One-dimensional projections of the data and pre-fit SM predictions in ${N_{{\mathrm{b}}\text {-jet}}}$ after applying additional selection criteria, given in the figure legends, to enhance the sensitivity to the T2tt signal process. The (unstacked) results for two example signal scenarios are shown, one with $ {\Delta m} \gg $ 0 and the other with $ {\Delta m} \approx $ 0, where ${\Delta m}$ is the difference between the gluino or squark mass and the sum of the masses of the particles into which it decays. |
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Figure 12-e:
One-dimensional projections of the data and pre-fit SM predictions in ${H_{\mathrm {T}}^{\text {miss}}}$ after applying additional selection criteria, given in the figure legends, to enhance the sensitivity to the T2bb signal process. The (unstacked) results for two example signal scenarios are shown, one with $ {\Delta m} \gg $ 0 and the other with $ {\Delta m} \approx $ 0, where ${\Delta m}$ is the difference between the gluino or squark mass and the sum of the masses of the particles into which it decays. |
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Figure 12-f:
One-dimensional projections of the data and pre-fit SM predictions in ${N_{\text {jet}}}$ after applying additional selection criteria, given in the figure legends, to enhance the sensitivity to the T2qq signal process. The (unstacked) results for two example signal scenarios are shown, one with $ {\Delta m} \gg $ 0 and the other with $ {\Delta m} \approx $ 0, where ${\Delta m}$ is the difference between the gluino or squark mass and the sum of the masses of the particles into which it decays. |
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Figure 13:
The 95% CL upper limits on the production cross sections of the (upper left) T1tttt, (upper right) T1bbbb, (lower left) T1qqqq, and (lower right) T5qqqqVV signal models as a function of the gluino and LSP masses ${m_{{\mathrm{\tilde{g}}}}}$ and ${m_{\tilde{\chi}^0_1}}$. The thick solid (black) curves show the observed exclusion limits assuming the approximate-NNLO+NNLL cross sections [71,72,73,74,75]. The thin solid (black) curves show the changes in these limits as the signal cross sections are varied by their theoretical uncertainties [93]. The thick dashed (red) curves present the expected limits under the background-only hypothesis, while the two sets of thin dotted (red) curves indicate the region containing 68 and 95% of the distribution of limits expected under this hypothesis. |
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Figure 13-a:
The 95% CL upper limits on the production cross sections of the T1tttt signal model as a function of the gluino and LSP masses ${m_{{\mathrm{\tilde{g}}}}}$ and ${m_{\tilde{\chi}^0_1}}$. The thick solid (black) curves show the observed exclusion limits assuming the approximate-NNLO+NNLL cross sections [71,72,73,74,75]. The thin solid (black) curves show the changes in these limits as the signal cross sections are varied by their theoretical uncertainties [93]. The thick dashed (red) curves present the expected limits under the background-only hypothesis, while the two sets of thin dotted (red) curves indicate the region containing 68 and 95% of the distribution of limits expected under this hypothesis. |
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Figure 13-b:
The 95% CL upper limits on the production cross sections of the T1bbbb signal model as a function of the gluino and LSP masses ${m_{{\mathrm{\tilde{g}}}}}$ and ${m_{\tilde{\chi}^0_1}}$. The thick solid (black) curves show the observed exclusion limits assuming the approximate-NNLO+NNLL cross sections [71,72,73,74,75]. The thin solid (black) curves show the changes in these limits as the signal cross sections are varied by their theoretical uncertainties [93]. The thick dashed (red) curves present the expected limits under the background-only hypothesis, while the two sets of thin dotted (red) curves indicate the region containing 68 and 95% of the distribution of limits expected under this hypothesis. |
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Figure 13-c:
The 95% CL upper limits on the production cross sections of the T1qqqq signal model as a function of the gluino and LSP masses ${m_{{\mathrm{\tilde{g}}}}}$ and ${m_{\tilde{\chi}^0_1}}$. The thick solid (black) curves show the observed exclusion limits assuming the approximate-NNLO+NNLL cross sections [71,72,73,74,75]. The thin solid (black) curves show the changes in these limits as the signal cross sections are varied by their theoretical uncertainties [93]. The thick dashed (red) curves present the expected limits under the background-only hypothesis, while the two sets of thin dotted (red) curves indicate the region containing 68 and 95% of the distribution of limits expected under this hypothesis. |
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Figure 13-d:
The 95% CL upper limits on the production cross sections of the T5qqqqVV signal model as a function of the gluino and LSP masses ${m_{{\mathrm{\tilde{g}}}}}$ and ${m_{\tilde{\chi}^0_1}}$. The thick solid (black) curves show the observed exclusion limits assuming the approximate-NNLO+NNLL cross sections [71,72,73,74,75]. The thin solid (black) curves show the changes in these limits as the signal cross sections are varied by their theoretical uncertainties [93]. The thick dashed (red) curves present the expected limits under the background-only hypothesis, while the two sets of thin dotted (red) curves indicate the region containing 68 and 95% of the distribution of limits expected under this hypothesis. |
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Figure 14:
The 95% CL upper limits on the production cross sections of the (upper left) T2tt, (upper right) T2bb, and (lower) T2qq signal models as a function of the squark and LSP masses ${m_{\tilde{q}}}$ and ${m_{\tilde{\chi}^0_1}}$. The meaning of the curves is described in the Fig. 13 caption. For the T2tt model, we do not present cross section upper limits in the unshaded diagonal region at low ${m_{\tilde{\chi}^0_1}}$ for the reason discussed in the text. The diagonal dotted line shown for this model corresponds to $ {m_{\tilde{\mathrm{t}}}} - {m_{\tilde{\chi}^0_1}} = {m_{\mathrm{t}}} $. |
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Figure 14-a:
The 95% CL upper limits on the production cross sections of the T2tt signal models as a function of the squark and LSP masses ${m_{\tilde{q}}}$ and ${m_{\tilde{\chi}^0_1}}$. The meaning of the curves is described in the Fig. 13 caption. We do not present cross section upper limits in the unshaded diagonal region at low ${m_{\tilde{\chi}^0_1}}$ for the reason discussed in the text. The diagonal dotted line shown for this model corresponds to $ {m_{\tilde{\mathrm{t}}}} - {m_{\tilde{\chi}^0_1}} = {m_{\mathrm{t}}} $. |
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Figure 14-b:
The 95% CL upper limits on the production cross sections of the T2bb signal models as a function of the squark and LSP masses ${m_{\tilde{q}}}$ and ${m_{\tilde{\chi}^0_1}}$. The meaning of the curves is described in the Fig. 13 caption. |
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Figure 14-c:
The 95% CL upper limits on the production cross sections of the T2qq signal models as a function of the squark and LSP masses ${m_{\tilde{q}}}$ and ${m_{\tilde{\chi}^0_1}}$. The meaning of the curves is described in the Fig. 13 caption. |
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Figure 15:
The observed numbers of events and pre-fit SM background predictions in the aggregate search bins. The total background uncertainty is shown by the hatched regions. The lower panel displays the fractional differences between the data and the SM predictions. |
| Tables | |
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Table 1:
Definition of the search intervals in the ${H_{\mathrm {T}}^{\text {miss}}}$ and ${H_{\mathrm {T}}}$ variables. Intervals 1 and 4 are discarded for $ {N_{\text {jet}}} \geq $ 8. In addition, regions with $ {H_{\mathrm {T}}^{\text {miss}}} > {H_{\mathrm {T}}} $ are excluded as illustrated in Fig. 3. |
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Table 2:
Systematic uncertainties in the yield of signal events, averaged over all search bins. The variations correspond to different signal models and choices for the SUSY particle masses. Results reported as 0.0 correspond to values less than 0.05%. |
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Table 3:
Observed number of events and pre-fit background predictions in the 2 $\leq {N_{\text {jet}}} \leq $ 3 search bins. For the background predictions, the first uncertainty is statistical and the second systematic. |
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Table 4:
Observed number of events and pre-fit background predictions in the 4 $\leq {N_{\text {jet}}} \leq $ 5 search bins. For the background predictions, the first uncertainty is statistical and the second systematic. |
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Table 5:
Observed number of events and pre-fit background predictions in the 6 $\leq {N_{\text {jet}}} \leq $ 7 search bins. For the background predictions, the first uncertainty is statistical and the second systematic. |
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Table 6:
Observed number of events and pre-fit background predictions in the 8 $\leq {N_{\text {jet}}} \leq $ 9 search bins. For the background predictions, the first uncertainty is statistical and the second systematic. |
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Table 7:
Observed number of events and pre-fit background predictions in the $ {N_{\text {jet}}} \geq $ 10 search bins. For the background predictions, the first uncertainty is statistical and the second systematic. |
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Table 8:
Targeted event topologies for the 12 aggregate search bins. The variable ${\Delta m}$ states the difference between the gluino or squark mass and the sum of the masses of the particles into which the gluino or squark decays. |
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Table 9:
Selection criteria, pre-fit background predictions, and observed number of events for the 12 aggregate search bins. For the background predictions, the first uncertainty is statistical and the second systematic. |
| Summary |
|
Using essentially the full CMS Run 2 data sample of proton-proton collisions at $\sqrt{s} = $ 13 TeV, corresponding to an integrated luminosity of 137 fb$^{-1}$ collected in 2016-2018, a search for supersymmetry has been performed based on events containing multiple jets and large missing transverse momentum. The event yields are measured in 174 nonoverlapping search bins defined in a four-dimensional space of missing transverse momentum (${H_{\mathrm{T}}^{\text{miss}}}$), the scalar sum of jet transverse momenta (${H_{\mathrm{T}}}$), the number of jets, and the number of tagged bottom quark jets. The events are required to satisfy ${H_{\mathrm{T}}^{\text{}}} > $ 300 GeV, ${H_{\mathrm{T}}} > $ 300 GeV, and to have at least two jets with transverse momentum ${p_{\mathrm{T}}} > $ 30 GeV. Events with isolated high ${p_{\mathrm{T}}}$ leptons or photons are vetoed. The results are compared to the expected number of background events from standard model (SM) processes. The principal backgrounds arise from events with neutrino production or jet mismeasurement. The SM background is evaluated using control regions in data supplemented by information from Monte Carlo event simulation. The observed event yields are found to be consistent with the SM background and no evidence for supersymmetry is obtained. The results are interpreted in the context of simplified models for gluino and squark pair production. For the gluino models, each of the produced gluinos decays either to a $\mathrm{t\bar{t}}$ pair and an undetected, stable, lightest supersymmetric particle, assumed to be the ${\tilde{\chi}^0_1}$ neutralino (T1tttt model); to a $\mathrm{b\bar{b}}$ pair and the ${\tilde{\chi}^0_1}$ (T1bbbb model); to a light-flavored (u, d, s, c) $\mathrm{q\bar{q}}$ pair and the ${\tilde{\chi}^0_1}$ (T1qqqq model); or to a light-flavored quark and antiquark and either the second-lightest neutralino $\tilde{\chi}^{0}_{2}$ or the lightest chargino $\tilde{\chi}_1^{\pm}$, followed by decay of the $\tilde{\chi}^{0}_{2}$ ($\tilde{\chi}_1^{\pm}$) to the $\tilde{\chi}^0_1$ and an on- or off-mass-shell Z ($\mathrm{W}^\pm$) boson (T5qqqqVV model). For the squark models, each of the produced squarks decays either to a top quark and the ${\tilde{\chi}^0_1}$ (T2tt model), to a bottom quark and the ${\tilde{\chi}^0_1}$ (T2bb model), or to a light-flavored quark and the ${\tilde{\chi}^0_1}$ (T2qq model). Using the predicted cross sections with next-to-leading order plus approximate next-to-leading logarithm accuracy as a reference, gluinos with masses as large as from 2000 to 2310 GeV are excluded at 95% confidence level, depending on the signal model. The corresponding limits on the masses of directly produced squarks range from 1190 for top squarks to 1630 GeV for light-flavored squarks. The results presented here supersede those of Ref. [7], extending the mass limits of this previous study by, typically, 200 GeV or more. |
| Additional Figures | |
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Additional Figure 1:
Observed event yields (solid points with error bars) overlaid with the post-fit background yield (stacked histograms). In each plot the lower panel shows the pull, defined as $(N_{\rm Obs.}-N_{\rm Post.})/\sqrt {N_{\rm Post.}+(\delta N_{\rm Post.})^2}$, where $\delta N_{\rm Post.}$ is the post-fit uncertainty on the corresponding background. |
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Additional Figure 2:
From left-to-right, one-dimensional projections of observed number of events and post-fit background distributions in the search region in ${H_{\mathrm T}^{\text {miss}}}$, ${N_{\text {jet}}}$, and ${N_{{{\mathrm {b}}}\text {-jet}}}$. The events in each distribution are integrated over the other three search variables and uncertainties are taken as fully correlated. |
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Additional Figure 2-a:
One-dimensional projection of observed number of events and post-fit background distributions in the search region in ${H_{\mathrm T}^{\text {miss}}}$. The events in each distribution are integrated over the other three search variables and uncertainties are taken as fully correlated. |
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Additional Figure 2-b:
One-dimensional projection of observed number of events and post-fit background distributions in the search region in ${N_{\text {jet}}}$. The events in each distribution are integrated over the other three search variables and uncertainties are taken as fully correlated. |
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Additional Figure 2-c:
One-dimensional projection of observed number of events and post-fit background distributions in the search region in ${N_{{{\mathrm {b}}}\text {-jet}}}$. The events in each distribution are integrated over the other three search variables and uncertainties are taken as fully correlated. |
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Additional Figure 3:
The observed significance of the SMS gluino models for T1tttt, T1bbbb, T1qqqq, and T5qqqqVV as function of the gluino and LSP masses. |
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Additional Figure 3-a:
The observed significance of the SMS gluino models for T1tttt as function of the gluino and LSP masses. |
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Additional Figure 3-b:
The observed significance of the SMS gluino models for T1bbbb as function of the gluino and LSP masses. |
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Additional Figure 3-c:
The observed significance of the SMS gluino models for T1qqqq as function of the gluino and LSP masses. |
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Additional Figure 3-d:
The observed significance of the SMS gluino models for T5qqqqVV as function of the gluino and LSP masses. |
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Additional Figure 4:
The observed significance of the SMS squark models for T2tt, T2bb, and T2qq as function of the squark and LSP masses. |
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Additional Figure 4-a:
The observed significance of the SMS squark models for T2tt as function of the squark and LSP masses. |
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Additional Figure 4-b:
The observed significance of the SMS squark models for T2bb as function of the squark and LSP masses. |
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Additional Figure 4-c:
The observed significance of the SMS squark models for T2qq as function of the squark and LSP masses. |
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Additional Figure 5:
The efficiency times acceptance of the SMS gluino models for T1tttt, T1bbbb, T1qqqq, and T5qqqqVV as function of the gluino and LSP masses. The efficiency times acceptance is given for the total signal across the set of 174 search regions. |
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Additional Figure 5-a:
The efficiency times acceptance of the SMS gluino models for T1tttt as function of the gluino and LSP masses. The efficiency times acceptance is given for the total signal across the set of 174 search regions. |
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Additional Figure 5-b:
The efficiency times acceptance of the SMS gluino models for T1bbbb as function of the gluino and LSP masses. The efficiency times acceptance is given for the total signal across the set of 174 search regions. |
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Additional Figure 5-c:
The efficiency times acceptance of the SMS gluino models for T1qqqq as function of the gluino and LSP masses. The efficiency times acceptance is given for the total signal across the set of 174 search regions. |
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Additional Figure 5-d:
The efficiency times acceptance of the SMS gluino models for T5qqqqVV as function of the gluino and LSP masses. The efficiency times acceptance is given for the total signal across the set of 174 search regions. |
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Additional Figure 6:
The efficiency times acceptance of the SMS squark models for T2tt, T2bb and T2qq as function of the squark and LSP masses. The efficiency times acceptance is given for the total signal across the set of 174 search regions. |
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Additional Figure 6-a:
The efficiency times acceptance of the SMS squark models for T2tt as function of the squark and LSP masses. The efficiency times acceptance is given for the total signal across the set of 174 search regions. |
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Additional Figure 6-b:
The efficiency times acceptance of the SMS squark models for T2bb as function of the squark and LSP masses. The efficiency times acceptance is given for the total signal across the set of 174 search regions. |
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Additional Figure 6-c:
The efficiency times acceptance of the SMS squark models for T2qq as function of the squark and LSP masses. The efficiency times acceptance is given for the total signal across the set of 174 search regions. |
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Additional Figure 7:
Pre-fit background covariance matrix $\sigma _{xy}$ and correlation matrix $\rho _{correl}$ |
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Additional Figure 7-a:
Pre-fit background covariance matrix $\sigma _{xy}$. |
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Additional Figure 7-b:
Pre-fit background correlation matrix $\rho _{correl}$. |
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Additional Figure 8:
Event displays for a SUSY candidate event with 12 jets in the search region, 273447:179:291867669 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 momenta of the b-tagged jets are marked in green. |
png pdf |
Additional Figure 8-a:
Event display for a SUSY candidate event with 12 jets in the search region, 273447:179:291867669 in $r-\phi $ view. The momenta of the non b-tagged jets are marked and labeled in orange and the momenta of the b-tagged jets are marked in green. |
png pdf |
Additional Figure 8-b:
Event display for a SUSY candidate event with 12 jets in the search region, 273447:179:291867669 in $r-\phi $ view with a white background. The momenta of the non b-tagged jets are marked and labeled in orange and the momenta of the b-tagged jets are marked in green. |
png pdf |
Additional Figure 8-c:
Event display for a SUSY candidate event with 12 jets in the search region, 273447:179:291867669 in 3D view. The momenta of the non b-tagged jets are marked and labeled in orange and the momenta of the b-tagged jets are marked in green. |
png pdf |
Additional Figure 8-d:
Event display for a SUSY candidate event with 12 jets in the search region, 273447:179:291867669 in 3D view with a white background. The momenta of the non b-tagged jets are marked and labeled in orange and the momenta of the b-tagged jets are marked in green. |
png pdf |
Additional Figure 9:
Event displays for a SUSY candidate event with very high $H_{\rm T}^{\rm miss}$ in the search region, 321219:344:504952772 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. |
png pdf |
Additional Figure 9-a:
Event display for a SUSY candidate event with very high $H_{\rm T}^{\rm miss}$ in the search region, 321219:344:504952772 in $r-\phi $ view. The momenta of the two jets are marked and labeled in orange. |
png pdf |
Additional Figure 9-b:
Event display for a SUSY candidate event with very high $H_{\rm T}^{\rm miss}$ in the search region, 321219:344:504952772 in $r-\phi $ view with a white background. The momenta of the two jets are marked and labeled in orange. |
png pdf |
Additional Figure 9-c:
Event display for a SUSY candidate event with very high $H_{\rm T}^{\rm miss}$ in the search region, 321219:344:504952772 in 3D view. The momenta of the two jets are marked and labeled in orange. |
png pdf |
Additional Figure 9-d:
Event display for a SUSY candidate event with very high $H_{\rm T}^{\rm miss}$ in the search region, 321219:344:504952772 in 3D view with a white background. The momenta of the two jets are marked and labeled in orange. |
png pdf |
Additional Figure 10:
Event displays for a T1bbbb-like candidate in the search region with exactly 4 jets, all of which are b-tagged, 321295:60:95701713 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. |
png pdf |
Additional Figure 10-a:
Event display for a T1bbbb-like candidate in the search region with exactly 4 jets, all of which are b-tagged, 321295:60:95701713 in $r-\phi $ view. The momenta of the four b-tagged jets are marked and labeled in green. |
png pdf |
Additional Figure 10-b:
Event display for a T1bbbb-like candidate in the search region with exactly 4 jets, all of which are b-tagged, 321295:60:95701713 in $r-\phi $ view with a white background. The momenta of the four b-tagged jets are marked and labeled in green. |
png pdf |
Additional Figure 10-c:
Event display for a T1bbbb-like candidate in the search region with exactly 4 jets, all of which are b-tagged, 321295:60:95701713 in 3D view. The momenta of the four b-tagged jets are marked and labeled in green. |
png pdf |
Additional Figure 10-d:
Event display for a T1bbbb-like candidate in the search region with exactly 4 jets, all of which are b-tagged, 321295:60:95701713 in 3D view with a white background. The momenta of the four b-tagged jets are marked and labeled in green. |
png pdf |
Additional Figure 11:
Distributions of (a) $H_{\rm T}$, (b) $H_{\rm T}^{\rm miss}$, (c) the number of jets, and (d) the number of b-tagged jets from four representative gluino pair production signal models with ${m_{{\mathrm {\tilde{g}}}} \gg m_{{\tilde{\chi}^{0}_{1}}}}$ after the baseline selection. Each plot ignores the baseline requirement (if any) for its respective variable. The last bin in each plot contains the overflow events. Only statistical uncertainties are shown. |
png pdf root |
Additional Figure 11-a:
Distribution of $H_{\rm T}$ from four representative gluino pair production signal models with ${m_{{\mathrm {\tilde{g}}}} \gg m_{{\tilde{\chi}^{0}_{1}}}}$ after the baseline selection. The last bin contains the overflow events. Only statistical uncertainties are shown. |
png pdf root |
Additional Figure 11-b:
Distribution of $H_{\rm T}^{\rm miss}$ from four representative gluino pair production signal models with ${m_{{\mathrm {\tilde{g}}}} \gg m_{{\tilde{\chi}^{0}_{1}}}}$ after the baseline selection. The last bin contains the overflow events. Only statistical uncertainties are shown. |
png pdf root |
Additional Figure 11-c:
Distribution of the number of jets from four representative gluino pair production signal models with ${m_{{\mathrm {\tilde{g}}}} \gg m_{{\tilde{\chi}^{0}_{1}}}}$ after the baseline selection. The last bin contains the overflow events. Only statistical uncertainties are shown. |
png pdf root |
Additional Figure 11-d:
Distribution of the number of b-tagged jets from four representative gluino pair production signal models with ${m_{{\mathrm {\tilde{g}}}} \gg m_{{\tilde{\chi}^{0}_{1}}}}$ after the baseline selection. The last bin contains the overflow events. Only statistical uncertainties are shown. |
png pdf |
Additional Figure 12:
Distributions of (a) $H_{\rm T}$, (b) $H_{\rm T}^{\rm miss}$, (c) the number of jets, and (d) the number of b-tagged jets from four representative gluino pair production signal models with ${m_{{\mathrm {\tilde{g}}}} \sim m_{{\tilde{\chi}^{0}_{1}}}}$ after the baseline selection. Each plot ignores the baseline requirement (if any) for its respective variable. The last bin in each plot contains the overflow events. Only statistical uncertainties are shown. |
png pdf root |
Additional Figure 12-a:
Distribution of $H_{\rm T}$ from four representative gluino pair production signal models with ${m_{{\mathrm {\tilde{g}}}} \sim m_{{\tilde{\chi}^{0}_{1}}}}$ after the baseline selection. The last bin contains the overflow events. Only statistical uncertainties are shown. |
png pdf root |
Additional Figure 12-b:
Distribution of $H_{\rm T}^{\rm miss}$ from four representative gluino pair production signal models with ${m_{{\mathrm {\tilde{g}}}} \sim m_{{\tilde{\chi}^{0}_{1}}}}$ after the baseline selection. The last bin contains the overflow events. Only statistical uncertainties are shown. |
png pdf root |
Additional Figure 12-c:
Distribution of the number of jets from four representative gluino pair production signal models with ${m_{{\mathrm {\tilde{g}}}} \sim m_{{\tilde{\chi}^{0}_{1}}}}$ after the baseline selection. The last bin contains the overflow events. Only statistical uncertainties are shown. |
png pdf root |
Additional Figure 12-d:
Distribution of the number of b-tagged jets from four representative gluino pair production signal models with ${m_{{\mathrm {\tilde{g}}}} \sim m_{{\tilde{\chi}^{0}_{1}}}}$ after the baseline selection. The last bin contains the overflow events. Only statistical uncertainties are shown. |
png pdf |
Additional Figure 13:
Distributions of (a) $H_{\rm T}$, (b) $H_{\rm T}^{\rm miss}$, (c) the number of jets, and (d) the number of b-tagged jets from three representative squark pair production signal models with ${m_{{\tilde{\mathrm {q}}}} \gg m_{{\tilde{\chi}^{0}_{1}}}}$ after the baseline selection. Each plot ignores the baseline requirement (if any) for its respective variable. The last bin in each plot contains the overflow events. Only statistical uncertainties are shown. |
png pdf root |
Additional Figure 13-a:
Distribution of $H_{\rm T}$ from three representative squark pair production signal models with ${m_{{\tilde{\mathrm {q}}}} \gg m_{{\tilde{\chi}^{0}_{1}}}}$ after the baseline selection. The last bin contains the overflow events. Only statistical uncertainties are shown. |
png pdf root |
Additional Figure 13-b:
Distribution of $H_{\rm T}^{\rm miss}$ from three representative squark pair production signal models with ${m_{{\tilde{\mathrm {q}}}} \gg m_{{\tilde{\chi}^{0}_{1}}}}$ after the baseline selection. The last bin contains the overflow events. Only statistical uncertainties are shown. |
png pdf root |
Additional Figure 13-c:
Distribution of the number of jets from three representative squark pair production signal models with ${m_{{\tilde{\mathrm {q}}}} \gg m_{{\tilde{\chi}^{0}_{1}}}}$ after the baseline selection. The last bin contains the overflow events. Only statistical uncertainties are shown. |
png pdf root |
Additional Figure 13-d:
Distribution of the number of b-tagged jets from three representative squark pair production signal models with ${m_{{\tilde{\mathrm {q}}}} \gg m_{{\tilde{\chi}^{0}_{1}}}}$ after the baseline selection. The last bin contains the overflow events. Only statistical uncertainties are shown. |
png pdf |
Additional Figure 14:
Distributions of (a) $H_{\rm T}$, (b) $H_{\rm T}^{\rm miss}$, (c) the number of jets, and (d) the number of b-tagged jets from three representative squark pair production signal models with ${m_{{\tilde{\mathrm {q}}}} \sim m_{{\tilde{\chi}^{0}_{1}}}}$ after the baseline selection. Each plot ignores the baseline requirement (if any) for its respective variable. The last bin in each plot contains the overflow events. Only statistical uncertainties are shown. |
png pdf root |
Additional Figure 14-a:
Distribution of $H_{\rm T}$ from three representative squark pair production signal models with ${m_{{\tilde{\mathrm {q}}}} \sim m_{{\tilde{\chi}^{0}_{1}}}}$ after the baseline selection. The last bin contains the overflow events. Only statistical uncertainties are shown. |
png pdf root |
Additional Figure 14-b:
Distribution of $H_{\rm T}^{\rm miss}$ from three representative squark pair production signal models with ${m_{{\tilde{\mathrm {q}}}} \sim m_{{\tilde{\chi}^{0}_{1}}}}$ after the baseline selection. The last bin contains the overflow events. Only statistical uncertainties are shown. |
png pdf root |
Additional Figure 14-c:
Distribution of the number of jets from three representative squark pair production signal models with ${m_{{\tilde{\mathrm {q}}}} \sim m_{{\tilde{\chi}^{0}_{1}}}}$ after the baseline selection. The last bin contains the overflow events. Only statistical uncertainties are shown. |
png pdf root |
Additional Figure 14-d:
Distribution of the number of b-tagged jets from three representative squark pair production signal models with ${m_{{\tilde{\mathrm {q}}}} \sim m_{{\tilde{\chi}^{0}_{1}}}}$ after the baseline selection. The last bin contains the overflow events. Only statistical uncertainties are shown. |
| Additional Tables | |
png pdf |
Additional Table 1:
Observed numbers of events and post-fit backgrounds in the 2 $\geq {N_{\text {jet}}} \geq $ 3 search regions. |
png pdf |
Additional Table 2:
Observed numbers of events and post-fit backgrounds in the 4 $\geq {N_{\text {jet}}} \geq $ 5 search regions. |
png pdf |
Additional Table 3:
Observed numbers of events and post-fit backgrounds in the 6 $\geq {N_{\text {jet}}} \geq $ 7 search regions. |
png pdf |
Additional Table 4:
Observed numbers of events and post-fit backgrounds in the 8 $ \geq {N_{\text {jet}}} \geq $ 9 search regions. |
png pdf |
Additional Table 5:
Observed numbers of events and post-fit backgrounds in the $ {N_{\text {jet}}} \geq $ 10 search regions. |
png pdf |
Additional Table 6:
Observed numbers of events and prefit background predictions in the aggregate search regions. The first uncertainty is statistical and second systematic. |
png pdf |
Additional Table 7:
Signal yields for representative gluino signal model points in the aggregate search regions. The uncertainties shown are statistical. |
png pdf |
Additional Table 8:
Signal yields for representative squark signal model points in the aggregate search regions. The uncertainties shown are statistical. |
png pdf |
Additional Table 9:
Absolute cumulative efficiencies in % for each step of the event selection process, listed for four representative gluino pair production signal models with ${m_{{\mathrm {\tilde{g}}}} \gg m_{{\tilde{\chi}^{0}_{1}}}}$. Only statistical uncertainties are shown. |
png pdf |
Additional Table 10:
Absolute cumulative efficiencies in % for each step of the event selection process, listed for four representative gluino pair production signal models with ${m_{{\mathrm {\tilde{g}}}} \sim m_{{\tilde{\chi}^{0}_{1}}}}$. Only statistical uncertainties are shown. |
png pdf |
Additional Table 11:
Absolute cumulative efficiencies in % for each step of the event selection process, listed for three representative squark pair production signal models with ${m_{{\tilde{\mathrm {q}}}} \gg m_{{\tilde{\chi}^{0}_{1}}}}$. Only statistical uncertainties are shown. |
png pdf |
Additional Table 12:
Absolute cumulative efficiencies in % for each step of the event selection process, listed for three representative squark pair production signal models with ${m_{{\tilde{\mathrm {q}}}} \sim m_{{\tilde{\chi}^{0}_{1}}}}$. Only statistical uncertainties are shown. |
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