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CMS-PAS-SUS-19-006
Search for supersymmetry in proton-proton collisions at 13 TeV in final states with jets and missing transverse momentum
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 s= 13 TeV collected with the CMS detector in 2016-2018, corresponding to an integrated luminosity of 137 fb1, 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.
Figures & Tables Summary References CMS Publications
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 with direct gluino pair production.

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Figure 1-b:
Diagram for the T1bbbb simplified model with direct gluino pair production.

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Figure 1-c:
Diagram for the T1qqqq simplified model with direct gluino pair production.

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Figure 1-d:
Diagram for the T5qqqqVV simplified model with 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 with direct squark pair production.

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Figure 2-b:
Diagram for the T2bb simplified model with direct squark pair production.

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Figure 2-c:
Diagram for the T2qq simplified model with direct squark pair production.

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Figure 3:
Schematic illustration of the 10 kinematic search intervals in the HmissT versus HT plane. The region above the red dashed line is excluded, as are all of regions 1 and 4 for Njet 8. The rightmost and topmost bins are unbounded, extending to HT= and HmissT=, respectively.

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Figure 4:
(upper) The number of lost-lepton events in simulation, integrated over HT and HmissT, as a function of Njet and Nb-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 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 HT and HmissT.

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Figure 5:
Comparison of the directly simulated tˉt, single top quark, and W+jets background to the prediction obtained by treating the simulation like data, i.e., by applying the lost-lepton background determination procedure to the simulated single-lepton (e+μ) control region events. The 10 results (8 for Njet 8) within each region delineated by vertical dashed lines correspond sequentially to the 10 (8) kinematic intervals in HT and HmissT listed in Table 1 and Fig. 3. The ratio plot in the lower panel is obtained through bin-by-bin division of the corresponding results in the upper panels, including the uncertainties, by the central values of the predicted "treat simulation like data'' results. All uncertainties are statistical only.

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Figure 6:
(upper) The number of events in the γ+jets control region for data and simulation and (lower) the transfer factors RsimZνˉν/γ from simulation. The respective results are shown for the 46 search bins with Nb-jet= 0. The 10 results (8 for Njet 8) within each region delineated by vertical dashed lines correspond sequentially to the 10 (8) kinematic intervals in HT and HmissT 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 γ+jets and nonprompt MC event samples, where "nonprompt'' refers to SM MC events other than γ+jets. The simulated nonprompt results are dominated by events from the QCD sample. Because of limited statistic precision in the simulated event samples at large Njet, the transfer factors determined for the 8Njet9 region are also used for the Njet>10 region.

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Figure 7:
(upper) The observed event yield in the Z(+)+jets control region, integrated over HT and HmissT, as a function of Njet and Nb-jet. The uncertainties are statistical only. The stacked histograms show the corresponding results from simulation. (lower) The extrapolation factors Fdataj,b with their statistical uncertainties.

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Figure 8:
Prediction from simulation for the Z(+)+jets event yields in the 174 search bin space as determined by computing the Fdataj,b factors (Eq. (3)) and the Nb-jet= 0 event yields in the same manner as for data, in comparison to the corresponding direct Z(+)+jets prediction from simulation. The labeling of the bin numbers is the same as in Fig. 5. The pink bands show the statistical uncertainties in the prediction combined with the systematic uncertainty attributable to the kinematic (HT and HmissT) dependence. For bins corresponding to Nb-jet= 0, the agreement is exact by construction.

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Figure 9:
The observed and predicted distributions of (left) HmissT in the inverted-Δϕ control region and (right) HT in the low- HmissT 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 9-a:
The observed and predicted distributions of HmissT in the inverted-Δϕ control region. The uncertainties are statistical only. The lower panel shows 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 9-b:
The observed and predicted distributions of HT in the low- HmissT sideband. The uncertainties are statistical only. The lower panel shows 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 10:
Distribution of observed and predicted event yields in the inverted-Δϕ control region analysis bins. The uncertainties are statistical only. The labeling of the bin numbers is the same as in Fig. 5. 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 11:
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. 5. 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 12:
One-dimensional projections of the data and pre-fit SM predictions in HmissT, Njet, and Nb-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 Δm 0 and the other with Δm 0, where Δm 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 HmissT. 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 Δm 0 and the other with Δm 0, where Δm 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 Njet. 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 Δm 0 and the other with Δm 0, where Δm 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 Nb-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 Δm 0 and the other with Δm 0, where Δm 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:
One-dimensional projections of the data and pre-fit SM predictions in either HmissT, Njet, or Nb-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 Δm 0 and the other with Δm 0, where Δm 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-a:
One-dimensional projection of the data and pre-fit SM prediction in Njet after applying additional selection criteria, given in the figure legend, to enhance the sensitivity to the T1tttt signal process. The (unstacked) results for two example signal scenarios are shown in each instance, one with Δm 0 and the other with Δm 0, where Δm 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-b:
One-dimensional projection of the data and pre-fit SM prediction in Nb-jet after applying additional selection criteria, given in the figure legend, to enhance the sensitivity to the T1bbbb signal process. The (unstacked) results for two example signal scenarios are shown in each instance, one with Δm 0 and the other with Δm 0, where Δm 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-c:
One-dimensional projection of the data and pre-fit SM prediction in HmissT after applying additional selection criteria, given in the figure legend, to enhance the sensitivity to the T1qqqq signal process. The (unstacked) results for two example signal scenarios are shown in each instance, one with Δm 0 and the other with Δm 0, where Δm 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-d:
One-dimensional projection of the data and pre-fit SM prediction in Nb-jet after applying additional selection criteria, given in the figure legend, to enhance the sensitivity to the T2tt signal process. The (unstacked) results for two example signal scenarios are shown in each instance, one with Δm 0 and the other with Δm 0, where Δm 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-e:
One-dimensional projection of the data and pre-fit SM prediction in HmissT after applying additional selection criteria, given in the figure legend, to enhance the sensitivity to the T2bb signal process. The (unstacked) results for two example signal scenarios are shown in each instance, one with Δm 0 and the other with Δm 0, where Δm 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-f:
One-dimensional projection of the data and pre-fit SM prediction in Njet after applying additional selection criteria, given in the figure legend, to enhance the sensitivity to the T2qq signal process. The (unstacked) results for two example signal scenarios are shown in each instance, one with Δm 0 and the other with Δm 0, where Δm 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 14:
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˜g and m˜χ01. The thick solid (black) curves show the observed exclusion limits assuming the approximate-NNLO+NNLL cross sections [70,71,72,73,74]. The thin solid (black) curves show the changes in these limits as the signal cross sections are varied by their theoretical uncertainties [92]. 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-a:
The 95% CL upper limits on the production cross section of the T1tttt signal model as a function of the gluino and LSP masses m˜g and m˜χ01. The thick solid (black) curves show the observed exclusion limits assuming the approximate-NNLO+NNLL cross sections [70,71,72,73,74]. The thin solid (black) curves show the changes in these limits as the signal cross sections are varied by their theoretical uncertainties [92]. 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-b:
The 95% CL upper limits on the production cross section of the T1bbbb = signal model as a function of the gluino and LSP masses m˜g and m˜χ01. The thick solid (black) curves show the observed exclusion limits assuming the approximate-NNLO+NNLL cross sections [70,71,72,73,74]. The thin solid (black) curves show the changes in these limits as the signal cross sections are varied by their theoretical uncertainties [92]. 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-c:
The 95% CL upper limits on the production cross section of the T1qqqq signal model as a function of the gluino and LSP masses m˜g and m˜χ01. The thick solid (black) curves show the observed exclusion limits assuming the approximate-NNLO+NNLL cross sections [70,71,72,73,74]. The thin solid (black) curves show the changes in these limits as the signal cross sections are varied by their theoretical uncertainties [92]. 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-d:
The 95% CL upper limits on the production cross section of the T5qqqqVV signal model as a function of the gluino and LSP masses m˜g and m˜χ01. The thick solid (black) curves show the observed exclusion limits assuming the approximate-NNLO+NNLL cross sections [70,71,72,73,74]. The thin solid (black) curves show the changes in these limits as the signal cross sections are varied by their theoretical uncertainties [92]. 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 15:
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˜q and m˜χ01. The meaning of the curves is described in the Fig. 14 caption. For the T2tt model, we do not present cross section upper limits in the unshaded diagonal region at low m˜χ01 for the reason discussed in the text. The diagonal dotted line shown for this model corresponds to m˜tm˜χ01=mt.

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Figure 15-a:
The 95% CL upper limits on the production cross section of the T2tt signal model as a function of the squark and LSP masses m˜q and m˜χ01. The meaning of the curves is described in the Fig. 14 caption. We do not present cross section upper limits in the unshaded diagonal region at low m˜χ01 for the reason discussed in the text. The diagonal dotted line shown for this model corresponds to m˜tm˜χ01=mt.

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Figure 15-b:
The 95% CL upper limits on the production cross section of the T2bb signal model as a function of the squark and LSP masses m˜q and m˜χ01. The meaning of the curves is described in the Fig. 14 caption.

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Figure 15-c:
The 95% CL upper limits on the production cross section of the T2qq signal model as a function of the squark and LSP masses m˜q and m˜χ01. The meaning of the curves is described in the Fig. 14 caption.

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Figure 16:
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 HmissT and HT variables. Intervals 1 and 4 are discarded for Njet 8.

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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 Njet 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 Njet 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 Njet 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 Njet 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 Njet 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.

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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 s= 13 TeV, corresponding to an integrated luminosity of 137 fb1 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 (HmissT), the scalar sum of jet transverse momenta (HT), the number of jets, and the number of tagged bottom quark jets. The events are required to satisfy HmissT> 300 GeV, HT> 300 GeV, and to have at least two jets with transverse momentum pT> 30 GeV. Events with isolated high pT leptons or photons are vetoed.

The results are compared to the expected number of background events from standard model (SM) processes. The principal backgrounds are 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 tˉt pair and an undetected, stable, lightest-supersymmetric-particle, assumed to be the ˜χ01 neutralino (T1tttt model); to a bˉb pair and the ˜χ01 (T1bbbb model); to a light-flavored (u, d, s, c) qˉq pair and the ˜χ01 (T1qqqq model); or to a light-flavored quark and antiquark and either the second-lightest neutralino ˜χ02 or the lightest chargino ˜χ±1, followed by decay of the ˜χ02 (˜χ±1) to the ˜χ01 and an on- or off-shell Z (W) boson (T5qqqqVV model). For the squark models, each of the produced squarks decays either to a top quark and the ˜χ01 (T2tt model), to a bottom quark and the ˜χ01 (T2bb model), or to a light-flavored quark and the ˜χ01 (T2qq model).

Using the predicted cross sections with next-to-leading order plus 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.
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