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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 | ||
| CMS Collaboration | ||
| July 2019 | ||
| 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. | ||
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These preliminary results are superseded in this paper, JHEP 10 (2019) 244. The superseded preliminary plots can be found here. |
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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 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 ${H_{\mathrm {T}}^{\text {miss}}}$ versus ${H_{\mathrm {T}}}$ plane. The region above the red dashed line 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 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:
Comparison of the directly simulated ${\mathrm{t} {}\mathrm{\bar{t}}}$, 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+$\mu$) control region events. 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 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 ${\gamma}$+jets control region for data and simulation and (lower) the 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 statistic 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 7:
(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 8:
Prediction from simulation for the ${{\mathrm{Z} (\to \ell ^{+} \ell ^{-})}\,+jets}$ event yields in the 174 search bin space 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 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 (${H_{\mathrm {T}}}$ and ${H_{\mathrm {T}}^{\text {miss}}}$) dependence. For bins corresponding to $ {N_{{\mathrm{b}}\text {-jet}}} = $ 0, the agreement is exact by construction. |
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Figure 9:
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 9-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 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 ${H_{\mathrm {T}}}$ in the low- ${H_{\mathrm {T}}^{\text {miss}}}$ 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-$ {\Delta \phi}$ 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 ${H_{\mathrm {T}}^{\text {miss}}}$, ${N_{\text {jet}}}$, 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 12-a:
One-dimensional projections 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 12-b:
One-dimensional projections 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 12-c:
One-dimensional projections 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 13:
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 13-a:
One-dimensional projection of the data and pre-fit SM prediction in ${N_{\text {jet}}}$ 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 $ {\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-b:
One-dimensional projection of the data and pre-fit SM prediction in ${N_{{\mathrm{b}}\text {-jet}}}$ 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 $ {\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-c:
One-dimensional projection of the data and pre-fit SM prediction in ${H_{\mathrm {T}}^{\text {miss}}}$ 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 $ {\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-d:
One-dimensional projection of the data and pre-fit SM prediction in ${N_{{\mathrm{b}}\text {-jet}}}$ 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 $ {\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-e:
One-dimensional projection of the data and pre-fit SM prediction in ${H_{\mathrm {T}}^{\text {miss}}}$ 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 $ {\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-f:
One-dimensional projection of the data and pre-fit SM prediction in ${N_{\text {jet}}}$ 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 $ {\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 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 ${m_{{\mathrm{\tilde{g}}}}}$ and $ {m_{\tilde{\chi}_1^0}}$. 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 ${m_{{\mathrm{\tilde{g}}}}}$ and $ {m_{\tilde{\chi}_1^0}}$. 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 ${m_{{\mathrm{\tilde{g}}}}}$ and $ {m_{\tilde{\chi}_1^0}}$. 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 ${m_{{\mathrm{\tilde{g}}}}}$ and $ {m_{\tilde{\chi}_1^0}}$. 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 ${m_{{\mathrm{\tilde{g}}}}}$ and $ {m_{\tilde{\chi}_1^0}}$. 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 ${m_{\tilde{\mathrm{q}}}}$ and $ {m_{\tilde{\chi}_1^0}}$. 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_{\tilde{\chi}_1^0}}$ for the reason discussed in the text. The diagonal dotted line shown for this model corresponds to $ {m_{\tilde{\mathrm{t}}}} - {m_{\tilde{\chi}_1^0}} = {m_{\mathrm{t}}} $. |
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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 ${m_{\tilde{\mathrm{q}}}}$ and $ {m_{\tilde{\chi}_1^0}}$. 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_{\tilde{\chi}_1^0}}$ for the reason discussed in the text. The diagonal dotted line shown for this model corresponds to $ {m_{\tilde{\mathrm{t}}}} - {m_{\tilde{\chi}_1^0}} = {m_{\mathrm{t}}} $. |
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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 ${m_{\tilde{\mathrm{q}}}}$ and $ {m_{\tilde{\chi}_1^0}}$. 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 ${m_{\tilde{\mathrm{q}}}}$ and $ {m_{\tilde{\chi}_1^0}}$. 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 ${H_{\mathrm {T}}^{\text {miss}}}$ and ${H_{\mathrm {T}}}$ variables. Intervals 1 and 4 are discarded for $ {N_{\text {jet}}} \geq $ 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 $\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. |
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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 {miss}}} > $ 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 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 $\mathrm{t\bar{t}}$ 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-shell Z (W) 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 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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