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| CMS-SUS-16-036 ; CERN-EP-2017-084 | ||
| Search for new phenomena with the $ \mathrm{ M_{\mathrm T2} } $ variable in the all-hadronic final state produced in proton-proton collisions at $\sqrt{s} = $ 13 TeV | ||
| CMS Collaboration | ||
| 12 May 2017 | ||
| Eur. Phys. J C 77 (2017) 710 | ||
| Abstract: A search for new phenomena is performed using events with jets and significant transverse momentum imbalance, as inferred through the $M_{\mathrm{{T2}}}$ variable. The results are based on a sample of proton-proton collisions collected in 2016 at a center-of-mass energy of 13 TeV with the CMS detector and corresponding to an integrated luminosity of 35.9 fb$^{-1}$. No excess event yield is observed above the predicted standard model background, and the results are interpreted as limits on the masses of predicted particles in a variety of simplified models of $R$-parity conserving supersymmetry. Depending on the details of the model, 95% confidence level lower limits on the gluino (light-flavor squark) masses are placed up to 2025 (1550) GeV. Mass limits as high as 1070 (1175) GeV are set on the masses of top (bottom) squarks. Information is provided to enable re-interpretation of these results, including model-independent limits on the number of non-standard model events for a set of simplified, inclusive search regions. | ||
| Links: e-print arXiv:1705.04650 [hep-ex] (PDF) ; CDS record ; inSPIRE record ; CADI line (restricted) ; | ||
| Figures & Tables | Summary | Additional Figures & Tables | References | CMS Publications |
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Additional information on efficiencies needed for reinterpretation of these results are available here. Additional technical material for CMS speakers can be found here. |
| Figures | |
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Figure 1:
Distributions of the $ {M_{\mathrm {T2}}} $ variable in data and simulation for the single-lepton control region selection, after normalizing the simulation to data in the control region bins of $ {H_{\mathrm {T}}} $, $ {N_{\mathrm {j}}} $, and $ {N_{\mathrm{ b } }} $ for events with no b-tagged jets (left), and events with at least one b-tagged jet (right). The hatched bands on the top panels show the MC statistical uncertainty, while the solid gray bands in the ratio plots show the systematic uncertainty in the $ {M_{\mathrm {T2}}} $ shape. |
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Figure 1-a:
Distributions of the $ {M_{\mathrm {T2}}} $ variable in data and simulation for the single-lepton control region selection, after normalizing the simulation to data in the control region bins of $ {H_{\mathrm {T}}} $, $ {N_{\mathrm {j}}} $, and $ {N_{\mathrm{ b } }} $ for events with no b-tagged jets. The hatched bands on the top panels show the MC statistical uncertainty, while the solid gray bands in the ratio plots show the systematic uncertainty in the $ {M_{\mathrm {T2}}} $ shape. |
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Figure 1-b:
Distributions of the $ {M_{\mathrm {T2}}} $ variable in data and simulation for the single-lepton control region selection, after normalizing the simulation to data in the control region bins of $ {H_{\mathrm {T}}} $, $ {N_{\mathrm {j}}} $, and $ {N_{\mathrm{ b } }} $ for events with at least one b-tagged jet. The hatched bands on the top panels show the MC statistical uncertainty, while the solid gray bands in the ratio plots show the systematic uncertainty in the $ {M_{\mathrm {T2}}} $ shape. |
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Figure 2:
(Left) Ratio $R^{\mathrm {SF}/\mathrm {OF}}$ in data as a function of $ {N_{\mathrm {j}}} $. The solid black line enclosed by the red dashed lines corresponds to a value of 1.13 $\pm$ 0.15 that is observed to be stable with respect to event kinematics, while the two dashed black lines denote the statistical uncertainty in the $R^{\mathrm {SF}/\mathrm {OF}}$ value. (Right) The shape of the $ {M_{\mathrm {T2}}} $ distribution in ${\mathrm{ Z } \to \nu \bar{\nu} }$ simulation compared to shapes from $\gamma $, W, and Z data control samples in a region with 1000 $ < {H_{\mathrm {T}}} < $ 1500 GeV and $ {N_{\mathrm {j}}} \ge $ 2, inclusive in $ {N_{\mathrm{ b } }} $. The solid gray band on the ratio plot shows the systematic uncertainty in the $ {M_{\mathrm {T2}}} $ shape. |
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Figure 2-a:
Ratio $R^{\mathrm {SF}/\mathrm {OF}}$ in data as a function of $ {N_{\mathrm {j}}} $. The solid black line enclosed by the red dashed lines corresponds to a value of 1.13 $\pm$ 0.15 that is observed to be stable with respect to event kinematics, while the two dashed black lines denote the statistical uncertainty in the $R^{\mathrm {SF}/\mathrm {OF}}$ value. |
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Figure 2-b:
The shape of the $ {M_{\mathrm {T2}}} $ distribution in ${\mathrm{ Z } \to \nu \bar{\nu} }$ simulation compared to shapes from $\gamma $, W, and Z data control samples in a region with 1000 $ < {H_{\mathrm {T}}} < $ 1500 GeV and $ {N_{\mathrm {j}}} \ge $ 2, inclusive in $ {N_{\mathrm{ b } }} $. The solid gray band on the ratio plot shows the systematic uncertainty in the $ {M_{\mathrm {T2}}} $ shape. |
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Figure 3:
The ratio $r_{\phi }$ as a function of $ {M_{\mathrm {T2}}} $ for 1000 $ < {H_{\mathrm {T}}} < $ 1500 GeV (left). The superimposed fit is performed to the open circle data points. The black points represent the data before subtracting non-QCD contributions using simulation. Data point uncertainties are statistical only. The red line and the grey band around it show the result of the fit to a power-law function performed in the window 70 $ < {M_{\mathrm {T2}}} < $ 100 GeV and the associated fit uncertainty. Values of $f_\mathrm {j}$, the fraction of events in bin $ {N_{\mathrm {j}}} $, (middle) and $r_{\mathrm{ b } }$, the fraction of events in bin $ {N_{\mathrm {j}}} $ that fall in bin $ {N_{\mathrm{ b } }} $, (right) are measured in data after requiring $ {\Delta \phi _{\text {min}}} < $ 0.3 and 100 $ < {M_{\mathrm {T2}}} < $ 200 GeV. The hatched bands represent both statistical and systematic uncertainties. |
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Figure 3-a:
The ratio $r_{\phi }$ as a function of $ {M_{\mathrm {T2}}} $ for 1000 $ < {H_{\mathrm {T}}} < $ 1500 GeV. The superimposed fit is performed to the open circle data points. The black points represent the data before subtracting non-QCD contributions using simulation. Data point uncertainties are statistical only. The red line and the grey band around it show the result of the fit to a power-law function performed in the window 70 $ < {M_{\mathrm {T2}}} < $ 100 GeV and the associated fit uncertainty. |
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Figure 3-b:
Values of $f_\mathrm {j}$, the fraction of events in bin $ {N_{\mathrm {j}}} $, are measured in data after requiring $ {\Delta \phi _{\text {min}}} < $ 0.3 and 100 $ < {M_{\mathrm {T2}}} < $ 200 GeV. The hatched band represents both statistical and systematic uncertainties. |
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Figure 3-c:
Values of $r_{\mathrm{ b } }$, the fraction of events in bin $ {N_{\mathrm {j}}} $ that fall in bin $ {N_{\mathrm{ b } }} $, are measured in data after requiring $ {\Delta \phi _{\text {min}}} < $ 0.3 and 100 $ < {M_{\mathrm {T2}}} < $ 200 GeV. The hatched band represents both statistical and systematic uncertainties. |
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Figure 4:
(Upper) Comparison of estimated (pre-fit) background and observed data events in each topological region. Hatched bands represent the full uncertainty in the background estimate. The results shown for $ {N_{\mathrm {j}}} = $ 1 correspond to the monojet search regions binned in jet $ {p_{\mathrm {T}}} $, whereas for the multijet signal regions, the notations j, b indicate $ {N_{\mathrm {j}}} $, $ {N_{\mathrm{ b } }} $ labeling. (Lower) Same for individual $ {M_{\mathrm {T2}}} $ signal bins in the medium $ {H_{\mathrm {T}}} $ region. On the $x$-axis, the $ {M_{\mathrm {T2}}} $ binning is shown in units of GeV. |
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Figure 4-a:
Comparison of estimated (pre-fit) background and observed data events in each topological region. Hatched bands represent the full uncertainty in the background estimate. The results shown for $ {N_{\mathrm {j}}} = $ 1 correspond to the monojet search regions binned in jet $ {p_{\mathrm {T}}} $, whereas for the multijet signal regions, the notations j, b indicate $ {N_{\mathrm {j}}} $, $ {N_{\mathrm{ b } }} $ labeling. |
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Figure 4-b:
Comparison of estimated (pre-fit) background and observed data events Same for individual $ {M_{\mathrm {T2}}} $ signal bins in the medium $ {H_{\mathrm {T}}} $ region. On the $x$-axis, the $ {M_{\mathrm {T2}}} $ binning is shown in units of GeV. |
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Figure 5:
(Upper) Diagrams for the three scenarios of gluino-mediated bottom squark, top squark and light flavor squark production considered. (Middle) Diagrams for the direct production of bottom, top and light-flavor squark pairs. (Lower) Diagrams for three alternate scenarios of direct top squark production with different decay modes. For mixed decay scenarios, we assume a 50% branching fraction for each decay mode. |
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Figure 5-a:
Diagram for the scenario of gluino-mediated bottom squark production considered. |
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Figure 5-b:
Diagram for the scenario of gluino-mediated top squark production considered. |
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Figure 5-c:
Diagram for the scenario of gluino-mediated light flavor squark production considered. |
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Figure 5-d:
Diagram for the direct production of bottom squark pairs. |
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Figure 5-e:
Diagram for the direct production of top squark pairs. |
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Figure 5-f:
Diagram for the direct production of light-flavor squark pairs. |
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Figure 5-g:
Diagram for an alternate scenario of direct top squark production with different decay modes. |
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Figure 5-h:
Diagram for an alternate scenario of direct top squark production with different decay modes. |
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Figure 5-i:
Diagram for an alternate scenario of direct top squark production with different decay modes. |
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Figure 6:
Exclusion limits at 95% CL for gluino-mediated bottom squark production (above left), gluino-mediated top squark production (above right), and gluino-mediated light-flavor (u, d, s, c) squark production (below). The area enclosed by the thick black curve represents the observed exclusion region, while the dashed red lines indicate the expected limits and their $\pm $1 standard deviation ranges. The thin black lines show the effect of the theoretical uncertainties on the signal cross section. |
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Figure 6-a:
Exclusion limits at 95% CL for gluino-mediated bottom squark production. The area enclosed by the thick black curve represents the observed exclusion region, while the dashed red lines indicate the expected limits and their $\pm $1 standard deviation ranges. The thin black lines show the effect of the theoretical uncertainties on the signal cross section. |
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Figure 6-b:
Exclusion limits at 95% CL for gluino-mediated top squark production. The area enclosed by the thick black curve represents the observed exclusion region, while the dashed red lines indicate the expected limits and their $\pm $1 standard deviation ranges. The thin black lines show the effect of the theoretical uncertainties on the signal cross section. |
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Figure 6-c:
Exclusion limits at 95% CL for gluino-mediated light-flavor (u, d, s, c) squark production. The area enclosed by the thick black curve represents the observed exclusion region, while the dashed red lines indicate the expected limits and their $\pm $1 standard deviation ranges. The thin black lines show the effect of the theoretical uncertainties on the signal cross section. |
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Figure 7:
Exclusion limit at 95% CL for bottom squark pair production (above left), top squark pair production (above right), and light-flavor squark pair production (below). The area enclosed by the thick black curve represents the observed exclusion region, while the dashed red lines indicate the expected limits and their $\pm $1 standard deviation ranges. For the top squark pair production plot, the $\pm $2 standard deviation ranges are also shown. The thin black lines show the effect of the theoretical uncertainties on the signal cross section. The white diagonal band in the upper right plot corresponds to the region $ {| m_{\tilde{ \mathrm{ t } } }-m_{\mathrm{ t } }-m_{\tilde{\chi}^0_1 } | }< $ 25 GeV and small $m_{\tilde{\chi}^0_1 }$. Here the efficiency of the selection is a strong function of $m_{\tilde{ \mathrm{ t } } }-m_{\tilde{\chi}^0_1 }$, and as a result the precise determination of the cross section upper limit is uncertain because of the finite granularity of the available MC samples in this region of the ($m_{\tilde{ \mathrm{ t } } }, m_{\tilde{\chi}^0_1 }$) plane. |
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Figure 7-a:
Exclusion limit at 95% CL for bottom squark pair production. The area enclosed by the thick black curve represents the observed exclusion region, while the dashed red lines indicate the expected limits and their $\pm $1 standard deviation ranges. |
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Figure 7-b:
Exclusion limit at 95% CL for top squark pair production. The area enclosed by the thick black curve represents the observed exclusion region, while the dashed red lines indicate the expected limits and their $\pm $1 standard deviation ranges. The $\pm $2 standard deviation ranges are also shown. The thin black lines show the effect of the theoretical uncertainties on the signal cross section. The white diagonal band corresponds to the region $ {| m_{\tilde{ \mathrm{ t } } }-m_{\mathrm{ t } }-m_{\tilde{\chi}^0_1 } | }< $ 25 GeV and small $m_{\tilde{\chi}^0_1 }$. Here the efficiency of the selection is a strong function of $m_{\tilde{ \mathrm{ t } } }-m_{\tilde{\chi}^0_1 }$, and as a result the precise determination of the cross section upper limit is uncertain because of the finite granularity of the available MC samples in this region of the ($m_{\tilde{ \mathrm{ t } } }, m_{\tilde{\chi}^0_1 }$) plane. |
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Figure 7-c:
Exclusion limit at 95% CL for light-flavor squark pair production. The area enclosed by the thick black curve represents the observed exclusion region, while the dashed red lines indicate the expected limits and their $\pm $1 standard deviation ranges. |
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Figure 8:
Exclusion limit at 95% CL for top squark pair production for different decay modes of the top squark. For the scenario where $\mathrm{ p } \mathrm{ p } \to \tilde{ \mathrm{ t } } \tilde{ \mathrm{t} } \to \mathrm{ b \bar{b} } \tilde{\chi}^{\pm}_1 {\tilde{\chi}^\mp _{1}} $, $\tilde{\chi}^{\pm}_1 \to \mathrm{ W } ^{\pm } \tilde{\chi}^0_1 $ (above left), the mass of the chargino is chosen to be half way in between the masses of the top squark and the neutralino. A mixed decay scenario (above right), $\mathrm{ p } \mathrm{ p } \to \tilde{ \mathrm{ t } } \tilde{ \mathrm{t} } $ with equal branching fractions for the top squark decays $\tilde{ \mathrm{ t } } \to \mathrm{ t } \tilde{\chi}^0_1 $ and $\tilde{ \mathrm{ t } } \to \mathrm{ b } \tilde{\chi}^{\pm}_1 $, $\tilde{\chi}^{\pm}_1 \to \mathrm{ W } ^{*+}\tilde{\chi}^0_1 $, is also considered, with the chargino mass chosen such that $\Delta m\left (\tilde{\chi}^{\pm}_1,\tilde{\chi}^0_1 \right) = $ 5 GeV. Finally, we also consider a compressed scenario (below) where $\mathrm{ p } \mathrm{ p } \to \tilde{ \mathrm{ t } } \tilde{ \mathrm{t} } \to \mathrm{c} \tilde{ \mathrm{c} } \tilde{\chi}^0_1 \tilde{\chi}^0_1 $. The area enclosed by the thick black curve represents the observed exclusion region, while the dashed red lines indicate the expected limits and their $\pm $1 standard deviation ranges. The thin black lines show the effect of the theoretical uncertainties on the signal cross section. |
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Figure 8-a:
Exclusion limit at 95% CL for top squark pair production for a scenario where $\mathrm{ p } \mathrm{ p } \to \tilde{ \mathrm{ t } } \tilde{ \mathrm{t} } \to \mathrm{ b \bar{b} } \tilde{\chi}^{\pm}_1 {\tilde{\chi}^\mp _{1}} $, $\tilde{\chi}^{\pm}_1 \to \mathrm{ W } ^{\pm } \tilde{\chi}^0_1 $, and where the mass of the chargino is chosen to be half way in between the masses of the top squark and the neutralino. The area enclosed by the thick black curve represents the observed exclusion region, while the dashed red lines indicate the expected limits and their $\pm $1 standard deviation ranges. The thin black lines show the effect of the theoretical uncertainties on the signal cross section. |
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Figure 8-b:
Exclusion limit at 95% CL for top squark pair production for a mixed decay scenario, $\mathrm{ p } \mathrm{ p } \to \tilde{ \mathrm{ t } } \tilde{ \mathrm{t} } $ with equal branching fractions for the top squark decays $\tilde{ \mathrm{ t } } \to \mathrm{ t } \tilde{\chi}^0_1 $ and $\tilde{ \mathrm{ t } } \to \mathrm{ b } \tilde{\chi}^{\pm}_1 $, $\tilde{\chi}^{\pm}_1 \to \mathrm{ W } ^{*+}\tilde{\chi}^0_1 $, with the chargino mass chosen such that $\Delta m\left (\tilde{\chi}^{\pm}_1,\tilde{\chi}^0_1 \right) = $ 5 GeV. The area enclosed by the thick black curve represents the observed exclusion region, while the dashed red lines indicate the expected limits and their $\pm $1 standard deviation ranges. The thin black lines show the effect of the theoretical uncertainties on the signal cross section. |
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Figure 8-c:
Exclusion limit at 95% CL for top squark pair production for a compressed scenario where $\mathrm{ p } \mathrm{ p } \to \tilde{ \mathrm{ t } } \tilde{ \mathrm{t} } \to \mathrm{c} \tilde{ \mathrm{c} } \tilde{\chi}^0_1 \tilde{\chi}^0_1 $. The area enclosed by the thick black curve represents the observed exclusion region, while the dashed red lines indicate the expected limits and their $\pm $1 standard deviation ranges. The thin black lines show the effect of the theoretical uncertainties on the signal cross section. |
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Figure 9:
(Upper) Comparison of the estimated background and observed data events in each signal bin in the monojet region. On the $x$-axis, the ${ {p_{\mathrm {T}}} ^{\text {jet1}}}$ binning is shown in units of GeV. Hatched bands represent the full uncertainty in the background estimate. (Lower) Same for the very low $ {H_{\mathrm {T}}} $ region. On the $x$-axis, the $ {M_{\mathrm {T2}}} $ binning is shown in units of GeV. |
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Figure 9-a:
Comparison of the estimated background and observed data events in each signal bin in the monojet region. On the $x$-axis, the ${ {p_{\mathrm {T}}} ^{\text {jet1}}}$ binning is shown in units of GeV. Hatched bands represent the full uncertainty in the background estimate. |
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Figure 9-b:
Comparison of the estimated background and observed data events in each signal bin in the very low $ {H_{\mathrm {T}}} $ region. On the $x$-axis, the $ {M_{\mathrm {T2}}} $ binning is shown in units of GeV. Hatched bands represent the full uncertainty in the background estimate. |
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Figure 10:
(Upper) Comparison of the estimated background and observed data events in each signal bin in the low-$ {H_{\mathrm {T}}} $ region. Hatched bands represent the full uncertainty in the background estimate. Same for the high- (middle) and extreme- (lower) $ {H_{\mathrm {T}}} $ regions. On the $x$-axis, the $ {M_{\mathrm {T2}}} $ binning is shown in units of GeV. For the extreme-$ {H_{\mathrm {T}}} $ region, the last bin is left empty for visualization purposes. |
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Figure 10-a:
Comparison of the estimated background and observed data events in the low-$ {H_{\mathrm {T}}} $ region. On the $x$-axis, the $ {M_{\mathrm {T2}}} $ binning is shown in units of GeV. Hatched bands represent the full uncertainty in the background estimate. |
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Figure 10-b:
Comparison of the estimated background and observed data events in the high-$ {H_{\mathrm {T}}} $ region. On the $x$-axis, the $ {M_{\mathrm {T2}}} $ binning is shown in units of GeV. Hatched bands represent the full uncertainty in the background estimate. |
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Figure 10-c:
Comparison of the estimated background and observed data events in the extreme-$ {H_{\mathrm {T}}} $ region. On the $x$-axis, the $ {M_{\mathrm {T2}}} $ binning is shown in units of GeV. The last bin is left empty for visualization purposes. Hatched bands represent the full uncertainty in the background estimate. |
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Figure 11:
Comparison of post-fit background prediction and observed data events in each topological region. Hatched bands represent the post-fit uncertainty in the background prediction. For the monojet, on the $x$-axis the $ { {p_{\mathrm {T}}} ^{\text {jet1}}} $ binning is shown in units of GeV, whereas for the multijet signal regions, the notations j, b indicate $ {N_{\mathrm {j}}} $, $ {N_{\mathrm{ b } }} $ labeling. |
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Figure 12:
(Upper) Comparison of the post-fit background prediction and observed data events in each signal bin in the monojet region. On the $x$-axis, the $ { {p_{\mathrm {T}}} ^{\text {jet1}}} $ binning is shown in units of GeV. (Middle) and (lower): Same for the very low and low-$ {H_{\mathrm {T}}} $ region. On the $x$-axis, the $ {M_{\mathrm {T2}}} $ binning is shown in units of GeV. The hatched bands represent the post-fit uncertainty in the background prediction. |
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Figure 12-a:
Comparison of the post-fit background prediction and observed data events in each signal bin in the monojet region. On the $x$-axis, the $ { {p_{\mathrm {T}}} ^{\text {jet1}}} $ binning is shown in units of GeV. The hatched bands represent the post-fit uncertainty in the background prediction. |
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Figure 12-b:
Comparison of the post-fit background prediction and observed data events in the very low-$ {H_{\mathrm {T}}} $ region. On the $x$-axis, the $ {M_{\mathrm {T2}}} $ binning is shown in units of GeV. The hatched bands represent the post-fit uncertainty in the background prediction. |
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Figure 12-c:
Comparison of the post-fit background prediction and observed data events in the low-$ {H_{\mathrm {T}}} $ region. On the $x$-axis, the $ {M_{\mathrm {T2}}} $ binning is shown in units of GeV. The hatched bands represent the post-fit uncertainty in the background prediction. |
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Figure 13:
(Upper) Comparison of the post-fit background prediction and observed data events in each signal bin in the medium-$ {H_{\mathrm {T}}} $ region. Same for the high- (middle) and extreme- (lower) $ {H_{\mathrm {T}}} $ regions. On the $x$-axis, the $ {M_{\mathrm {T2}}} $ binning is shown in units of GeV. The hatched bands represent the post-fit uncertainty in the background prediction. For the extreme-$ {H_{\mathrm {T}}} $ region, the last bin is left empty for visualization purposes. |
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Figure 13-a:
Comparison of the post-fit background prediction and observed data events in each signal bin in the medium-$ {H_{\mathrm {T}}} $ region. On the $x$-axis, the $ {M_{\mathrm {T2}}} $ binning is shown in units of GeV. The hatched bands represent the post-fit uncertainty in the background prediction. |
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Figure 13-b:
Comparison of the post-fit background prediction and observed data events in each signal bin in the high-$ {H_{\mathrm {T}}} $ region. On the $x$-axis, the $ {M_{\mathrm {T2}}} $ binning is shown in units of GeV. The hatched bands represent the post-fit uncertainty in the background prediction. |
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Figure 13-c:
Comparison of the post-fit background prediction and observed data events in each signal bin in the extreme-$ {H_{\mathrm {T}}} $ region. On the $x$-axis, the $ {M_{\mathrm {T2}}} $ binning is shown in units of GeV. The hatched bands represent the post-fit uncertainty in the background prediction. The last bin is left empty for visualization purposes. |
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Figure 14:
(Upper) The post-fit background prediction and observed data events in the analysis binning, for all topological regions with the expected yield for the signal model of gluino mediated bottom-squark production ($m_{\tilde{ \mathrm{g} } }= $ 1000 GeV, $m_{\tilde{\chi}^0_1 }= $ 800 GeV) stacked on top of the expected background. For the monojet regions, the $ { {p_{\mathrm {T}}} ^{\text {jet1}}} $ binning is in units of GeV. (Lower) Same for the extreme-$ {H_{\mathrm {T}}} $ region for the same signal with ($m_{\tilde{ \mathrm{g} } }= $ 1900 GeV, $m_{\tilde{\chi}^0_1 }= $ 100 GeV). On the $x$-axis, the $ {M_{\mathrm {T2}}} $ binning is shown in units of GeV. The hatched bands represent the post-fit uncertainty in the background prediction. For the extreme-$ {H_{\mathrm {T}}} $ region, the last bin is left empty for visualization purposes. |
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Figure 14-a:
The post-fit background prediction and observed data events in the analysis binning, for all topological regions with the expected yield for the signal model of gluino mediated bottom-squark production ($m_{\tilde{ \mathrm{g} } }= $ 1000 GeV, $m_{\tilde{\chi}^0_1 }= $ 800 GeV) stacked on top of the expected background. For the monojet regions, the $ { {p_{\mathrm {T}}} ^{\text {jet1}}} $ binning is in units of GeV. |
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Figure 14-b:
The post-fit background prediction and observed data events in the analysis binning, for the extreme-$ {H_{\mathrm {T}}} $ region for the signal with ($m_{\tilde{ \mathrm{g} } }= $ 1900 GeV, $m_{\tilde{\chi}^0_1 }= $ 100 GeV) stacked on top of the expected background. On the $x$-axis, the $ {M_{\mathrm {T2}}} $ binning is shown in units of GeV. The hatched bands represent the post-fit uncertainty in the background prediction. The last bin is left empty for visualization purposes. |
| Tables | |
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Table 1:
Summary of reconstruction objects and event preselection. Here $R$ is the distance parameter of the anti-$ {k_{\mathrm {T}}} $ algorithm. For veto leptons and tracks, the transverse mass $ {M_{\mathrm {T}}} $ is determined using the veto object and the ${\vec{p}_{\mathrm {T}}^{\text {miss}}} $, while $ {p_{\mathrm {T}}} ^{\text {sum}}$ denotes the sum of the transverse momenta of all the PF candidates in a cone around the lepton or track. The size of the cone, in units of $\Delta R \equiv \sqrt {{(\Delta \phi)^2 + (\Delta \eta)^2}}$ is given in the table. Further details of the lepton selection are described in Ref. [6]. The $i$th highest-$ {p_{\mathrm {T}}} $ jet is denoted as j$_i$. |
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Table 2:
Definitions of super signal regions, along with predictions, observed data, and the observed 95% CL upper limits on the number of signal events contributing to each region ($N_{95}^{\text {obs}}$). The limits are shown as a range corresponding to an assumed uncertainty in the signal acceptance of 0-15%. A dash in the selections means that no requirement is applied. |
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Table 3:
Typical values of the systematic uncertainties as evaluated for the simplified signal model of gluino-mediated bottom squark production, $\mathrm{ p } \mathrm{ p } \to \tilde{ \mathrm{g} } \tilde{ \mathrm{g} }, \tilde{ \mathrm{g} } \to {\mathrm{ b \bar{b} } } \tilde{\chi}^0_1 $. Uncertainties evaluated on other signal models are consistent with these ranges of values. The high statistical uncertainty in the simulated signal sample corresponds to a small number of signal bins with low acceptance, which are typically not among the most sensitive signal bins to that model point. |
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Table 4:
Summary of 95% CL observed exclusion limits on the masses of SUSY particles (sparticles) in different simplified model scenarios. The limit on the mass of the produced sparticle is quoted for a massless $\tilde{\chi}^0_1 $, while for the mass of the $\tilde{\chi}^0_1$ we quote the highest limit that is obtained. |
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Table 5:
Summary of signal regions for the monojet selection. |
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Table 6:
The $ {M_{\mathrm {T2}}} $ binning in each topological region of the multi-jet search regions, for the very low, low and medium $ {H_{\mathrm {T}}} $ regions. |
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Table 7:
The $ {M_{\mathrm {T2}}} $ binning in each topological region of the multijet search regions, for the high- and extreme-$ {H_{\mathrm {T}}} $ regions. |
| Summary |
| This paper presents the results of a search for new phenomena using events with jets and large ${M_{\mathrm{T2}}} $. Results are based on a 35.9 fb$ {^{-1}} $ data sample of proton-proton collisions at $\sqrt{s} =$ 13 TeV collected in 2016 with the CMS detector. No significant deviations from the standard model expectations are observed. The results are interpreted as limits on the production of new, massive colored particles in simplified models of supersymmetry. This search probes gluino masses up to 2025 GeV and ${\tilde{\chi}^{0}_{1}} $ masses up to 1400 GeV. Constraints are also obtained on the pair production of light-flavor, bottom, and top squarks, probing masses up to 1550, 1175, and 1070 GeV, respectively, and ${\tilde{\chi}^{0}_{1}}$ masses up to 775, 590, and 550 GeV in each scenario. |
| Additional Figures | |
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Additional Figure 1:
Full correlation (left) and covariance (right) matrices. |
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Additional Figure 1-a:
Full correlation matrix. |
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Additional Figure 1-b:
Full covariance matrix. |
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Additional Figure 2:
Observed significance for gluino-mediated bottom squark production model. A linear interpolation is performed across the plane, to account for the limited granularity of the simulated samples. Due to the non-linear nature of the significance, small fluctuations for single signal points may result into a visible effect on the plane. |
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Additional Figure 3:
Observed significance for gluino-mediated top squark production model. A linear interpolation is performed across the plane, to account for the limited granularity of the simulated samples. Due to the non-linear nature of the significance, small fluctuations for single signal points may result into a visible effect on the plane. |
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Additional Figure 4:
Observed significance for gluino-mediated light squark production model. A linear interpolation is performed across the plane, to account for the limited granularity of the simulated samples. Due to the non-linear nature of the significance, small fluctuations for single signal points may result into a visible effect on the plane. |
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Additional Figure 5:
Observed significance for direct bottom squark production model. A linear interpolation is performed across the plane, to account for the limited granularity of the simulated samples. Due to the non-linear nature of the significance, small fluctuations for single signal points may result into a visible effect on the plane. |
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Additional Figure 6:
Observed significance for direct top squark production model. A linear interpolation is performed across the plane, to account for the limited granularity of the simulated samples. Due to the non-linear nature of the significance, small fluctuations for single signal points may result into a visible effect on the plane. |
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Additional Figure 7:
Observed significance for direct light squark production model. A linear interpolation is performed across the plane, to account for the limited granularity of the simulated samples. Due to the non-linear nature of the significance, small fluctuations for single signal points may result into a visible effect on the plane. |
png pdf root |
Additional Figure 8:
Observed significance for direct top squark pair production model, for the scenario where $\mathrm{ p } \mathrm{ p } \to \tilde{ \mathrm{ t } }_1 \tilde{ \mathrm{ t } }_1^* \to \mathrm{ b \bar{b} } \tilde{\chi}^{\pm}_1 \tilde{\chi}^{\pm}_1 $, $\tilde{\chi}^{\pm}_1 \to \mathrm{ W } \tilde{\chi}^0_1 $, with the mass of the chargino chosen to be half way in between the masses of the top squark and the neutralino. A linear interpolation is performed across the plane, to account for the limited granularity of the simulated samples. Due to the non-linear nature of the significance, small fluctuations for single signal points may result into a visible effect on the plane. |
png pdf root |
Additional Figure 9:
Observed significance for direct top squark pair production model, for the scenario where $\mathrm{ p } \mathrm{ p } \to \tilde{ \mathrm{ t } }_1 \tilde{ \mathrm{ t } }_1^*\to \mathrm{ t } \mathrm{ b } \tilde{\chi}^{\pm}_1 \tilde{\chi}^0_1 $, $\tilde{\chi}^{\pm}_1 \to \mathrm{ W } ^{*}\tilde{\chi}^0_1 $, with the chargino mass chosen such that $\Delta m\left (\tilde{\chi}^{\pm}_1,\tilde{\chi}^0_1 \right) = $ 5 GeV. A linear interpolation is performed across the plane, to account for the limited granularity of the simulated samples. Due to the non-linear nature of the significance, small fluctuations for single signal points may result into a visible effect on the plane. |
png pdf root |
Additional Figure 10:
Observed significance for direct top squark pair production model, for a compressed scenario where $\mathrm{ p } \mathrm{ p } \to \tilde{ \mathrm{ t } }_1 \tilde{ \mathrm{ t } }_1^*\to \mathrm{c} \mathrm{ \bar{c} } \tilde{\chi}^0_1 \tilde{\chi}^0_1 $. A linear interpolation is performed across the plane, to account for the limited granularity of the simulated samples. Due to the non-linear nature of the significance, small fluctuations for single signal points may result into a visible effect on the plane. |
png pdf |
Additional Figure 11:
Summary of exclusion limits for gluino production models. |
png pdf |
Additional Figure 12:
Summary of exclusion limits for direct squark production models. |
png pdf |
Additional Figure 13:
Summary of exclusion limits for direct stop production models. |
| Additional Tables | |
png pdf |
Additional Table 1:
Cut flow table for basline selection and several sample additional kinematic selections for a signal model of gluino-mediated bottom squark production with the mass of the gluino and the LSP equal to 2100 and 1GeV, respectively. Theory cross section for this signal is 0.59 fb. |
png pdf |
Additional Table 2:
Cut flow table for basline selection and several sample additional kinematic selections for a signal model of gluino-mediated bottom squark production with the mass of the gluino and the LSP equal to 1800 and 1300GeV, respectively. Theory cross section for this signal is 2.76 fb. |
png pdf |
Additional Table 3:
Cut flow table for basline selection and several sample additional kinematic selections for a signal model of gluino-mediated top squark production with the mass of the gluino and the LSP equal to 1900 and 1GeV, respectively. Theory cross section for this signal is 1.64 fb. |
png pdf |
Additional Table 4:
Cut flow table for basline selection and several sample additional kinematic selections for a signal model of gluino-mediated top squark production with the mass of the gluino and the LSP equal to 1800 and 900GeV, respectively. Theory cross section for this signal is 2.76 fb. |
png pdf |
Additional Table 5:
Cut flow table for basline selection and several sample additional kinematic selections for a signal model of gluino-mediated light squark production with the mass of the gluino and the LSP equal to 1900 and 1GeV, respectively. Theory cross section for this signal is 1.64 fb. |
png pdf |
Additional Table 6:
Cut flow table for basline selection and several sample additional kinematic selections for a signal model of gluino-mediated light squark production with the mass of the gluino and the LSP equal to 1600 and 1000GeV, respectively. Theory cross section for this signal is 8.10 fb. |
png pdf |
Additional Table 7:
Cut flow table for basline selection and several sample additional kinematic selections for a signal model of direct bottom squark production with the mass of the squark and the LSP equal to 1200 and 1GeV, respectively. Theory cross section for this signal is 1.60 fb. |
png pdf |
Additional Table 8:
Cut flow table for basline selection and several sample additional kinematic selections for a signal model of direct bottom squark production with the mass of the squark and the LSP equal to 900 and 600GeV, respectively. Theory cross section for this signal is 12.9 fb. |
png pdf |
Additional Table 9:
Cut flow table for basline selection and several sample additional kinematic selections for a signal model of direct top squark production with the mass of the squark and the LSP equal to 1100 and 1GeV, respectively. Theory cross section for this signal is 3.07 fb. |
png pdf |
Additional Table 10:
Cut flow table for basline selection and several sample additional kinematic selections for a signal model of direct top squark production with the mass of the squark and the LSP equal to 500 and 400GeV, respectively. Theory cross section for this signal is 518 fb. |
png pdf |
Additional Table 11:
Cut flow table for basline selection and several sample additional kinematic selections for a signal model of direct light squark production with the mass of the squark and the LSP equal to 1500 and 1GeV, respectively. Theory cross section for this signal is 2.09 fb. |
png pdf |
Additional Table 12:
Cut flow table for basline selection and several sample additional kinematic selections for a signal model of direct light squark production with the mass of the squark and the LSP equal to 800 and 400GeV, respectively. Theory cross section for this signal is 231 fb. |
png pdf |
Additional Table 13:
Cut flow table for basline selection and several sample additional kinematic selections for a signal model of direct top squark production, where one top squark decays via a bottom quark while the other decays via a top quark, with the mass of the squark and the LSP equal to 900 and 1GeV, respectively. Theory cross section for this signal is 12.9 fb. |
png pdf |
Additional Table 14:
Cut flow table for basline selection and several sample additional kinematic selections for a signal model of direct top squark production, where one top squark decays via a bottom quark while the other decays via a top quark, with the mass of the squark and the LSP equal to 800 and 400GeV, respectively. Theory cross section for this signal is 28.3 fb. |
png pdf |
Additional Table 15:
Cut flow table for basline selection and several sample additional kinematic selections for a signal model of direct top squark production, where the top squark decays via a bottom quark, with the mass of the squark and the LSP equal to 900 and 1GeV, respectively. Theory cross section for this signal is 12.9 fb. |
png pdf |
Additional Table 16:
Cut flow table for basline selection and several sample additional kinematic selections for a signal model of direct top squark production, where the top squark decays via a bottom quark, with the mass of the squark and the LSP equal to 800 and 400GeV, respectively. Theory cross section for this signal is 28.3 fb. |
png pdf |
Additional Table 17:
Cut flow table for basline selection and several sample additional kinematic selections for a signal model of direct top squark production, where the top squark decays via a charm quark, with the mass of the squark and the LSP equal to 450 and 370GeV, respectively. Theory cross section for this signal is 948 fb. |
png pdf |
Additional Table 18:
Cut flow table for basline selection and several sample additional kinematic selections for a signal model of direct top squark production, where the top squark decays via a charm quark, with the mass of the squark and the LSP equal to 450 and 440GeV, respectively. Theory cross section for this signal is 948 fb. |
png pdf |
Additional Table 19:
Background estimate and observation in bins of jet $p_{\mathrm {T}}$ for the monojet regions. The yields correspond to an integrated luminosity of 35.9 fb$^{-1}$. |
png pdf |
Additional Table 20:
Background estimate and observation in bins of $M_{\mathrm {T2}}$ for 250 $ < H_{\mathrm {T}} < $ 450 GeV. The yields correspond to an integrated luminosity of 35.9 fb$^{-1}$. |
png pdf |
Additional Table 21:
Background estimate and observation in bins of $M_{\mathrm {T2}}$ for 450 $ < H_{\mathrm {T}} < $ 575 GeV. The yields correspond to an integrated luminosity of 35.9 fb$^{-1}$. |
png pdf |
Additional Table 22:
Background estimate and observation in bins of $M_{\mathrm {T2}}$ for 575 $ < H_{\mathrm {T}} < $ 1000 GeV. The yields correspond to an integrated luminosity of 35.9 fb$^{-1}$. |
png pdf |
Additional Table 23:
Background estimate and observation in bins of $M_{\mathrm {T2}}$ for 1000 $ < H_{\mathrm {T}} < $ 1500 GeV. The yields correspond to an integrated luminosity of 35.9 fb$^{-1}$. |
png pdf |
Additional Table 24:
Background estimate and observation in bins of $M_{\mathrm {T2}}$ for $H_{\mathrm {T}} > $ 1500 GeV. The yields correspond to an integrated luminosity of 35.9 fb$^{-1}$. |
|
Additional code to compute hemispheres and $M_{\mathrm{T2}}$ and an example of usage is available here.
The code available here also include python scripts to facilitate the access to the full covariance (correlation) matrix. One script allows to retrive the bin number on the covariance matrix axes for a given kinematic selection: with HT, jet pT, and/or MT2 expressed in GeV will return the bin number corresponding to the kinematic selection, together with the corresponding background predictions and observation. A second script allows to retrieve the kinematic selection corresponding to one bin number on the covariance matrix axes: will return the kinematic selection corresponding to the input bin number, together with the corresponding background predictions and observation. |
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