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CMS-PAS-EXO-22-020
Search for long-lived particles using displaced vertices and missing transverse momentum in proton-proton collisions at $ \sqrt{s}= $ 13 TeV
Abstract: A search for long-lived particles produced in proton-proton collisions at a center-of-mass energy of 13 TeV at the CERN LHC is presented. The search is based on data collected by the CMS experiment in 2016--2018 and corresponding to a total integrated luminosity of 137 fb$ ^{-1} $. This search is designed to be sensitive to long-lived particles with mean proper decay lengths between 0.1 and 1000 mm whose decay products produce a final state with at least one displaced vertex and missing transverse momentum. The observation is consistent with the standard model background prediction, and the results are used to constrain split supersymmetry models with different mean proper decay lengths and gluino masses. Gluinos with mean proper decay lengths between 1 and 100 mm are excluded at 95% confidence level in models for which the gluino mass is below 1800 and 2000 GeV when the difference in the gluino and neutrino masses is, respectively, 100 and 200 GeV. These limits are the most stringent to date for signal models with proper decay lengths up to 100 mm.
Figures & Tables Summary References CMS Publications
Figures

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Figure 1:
Diagram of the split SUSY signal model, showing a pair of long-lived gluinos that each decay to two quarks and one neutralino.

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Figure 2:
This diagram illustrates the architecture of the IN, where the flow of data is indicated by arrows. Rectangular boxes represent data matrices, while diamonds represent multilayer perceptrons (MLPs). The input information ($ O $) is integrated with relation matrices ($ R_{\text{r}} $, $ R_{\text{s}} $, and $ R_{\text{a}} $) to form a graph that captures interactions between tracks. This graph is subsequently processed by an MLP ($ \phi_{\text{R}} $) to compute the effect ($ E $) of the interactions. The effect is then combined with $ R_{\text{r}} $ and merged with the original input $ O $ to form $ C $. To assess the influence ($ P $) of the effect on the original information, it undergoes further processing via another MLP ($ \phi_{\text{O}} $). Finally, the influence is passed through an MLP ($ \phi_{\text{output}} $) and a sigmoid function to produce the final output.

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Figure 3:
Distributions of $ S_{\text{ML}} $ for simulated background and signal in the Run-2 dataset. Events with $ n_{\text{track}} $ of 3 (top), 4 (middle), and $ \geq $5 (bottom) are shown individually. The distributions are shown for split SUSY signals with a gluino mass of 2000 GeV and neutralino mass of 1900 GeV (left) and 1800 GeV (right). Different gluino proper decay lengths are shown as $ c\tau $ in the legend.

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Figure 3-a:
Distributions of $ S_{\text{ML}} $ for simulated background and signal in the Run-2 dataset. Events with $ n_{\text{track}} $ of 3 (top), 4 (middle), and $ \geq $5 (bottom) are shown individually. The distributions are shown for split SUSY signals with a gluino mass of 2000 GeV and neutralino mass of 1900 GeV (left) and 1800 GeV (right). Different gluino proper decay lengths are shown as $ c\tau $ in the legend.

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Figure 3-b:
Distributions of $ S_{\text{ML}} $ for simulated background and signal in the Run-2 dataset. Events with $ n_{\text{track}} $ of 3 (top), 4 (middle), and $ \geq $5 (bottom) are shown individually. The distributions are shown for split SUSY signals with a gluino mass of 2000 GeV and neutralino mass of 1900 GeV (left) and 1800 GeV (right). Different gluino proper decay lengths are shown as $ c\tau $ in the legend.

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Figure 3-c:
Distributions of $ S_{\text{ML}} $ for simulated background and signal in the Run-2 dataset. Events with $ n_{\text{track}} $ of 3 (top), 4 (middle), and $ \geq $5 (bottom) are shown individually. The distributions are shown for split SUSY signals with a gluino mass of 2000 GeV and neutralino mass of 1900 GeV (left) and 1800 GeV (right). Different gluino proper decay lengths are shown as $ c\tau $ in the legend.

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Figure 3-d:
Distributions of $ S_{\text{ML}} $ for simulated background and signal in the Run-2 dataset. Events with $ n_{\text{track}} $ of 3 (top), 4 (middle), and $ \geq $5 (bottom) are shown individually. The distributions are shown for split SUSY signals with a gluino mass of 2000 GeV and neutralino mass of 1900 GeV (left) and 1800 GeV (right). Different gluino proper decay lengths are shown as $ c\tau $ in the legend.

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Figure 3-e:
Distributions of $ S_{\text{ML}} $ for simulated background and signal in the Run-2 dataset. Events with $ n_{\text{track}} $ of 3 (top), 4 (middle), and $ \geq $5 (bottom) are shown individually. The distributions are shown for split SUSY signals with a gluino mass of 2000 GeV and neutralino mass of 1900 GeV (left) and 1800 GeV (right). Different gluino proper decay lengths are shown as $ c\tau $ in the legend.

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Figure 3-f:
Distributions of $ S_{\text{ML}} $ for simulated background and signal in the Run-2 dataset. Events with $ n_{\text{track}} $ of 3 (top), 4 (middle), and $ \geq $5 (bottom) are shown individually. The distributions are shown for split SUSY signals with a gluino mass of 2000 GeV and neutralino mass of 1900 GeV (left) and 1800 GeV (right). Different gluino proper decay lengths are shown as $ c\tau $ in the legend.

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Figure 4:
The distribution of $ n_{\text{track}} $ in different $ S_{\text{ML}} $ regions for simulated background events in Run-2. Events with 0 $ < S_{\text{ML}} < $ 0.2 (blue), 0.2 $ < S_{\text{ML}} < $ 0.6 (red), and 0.6 $ < S_{\text{ML}} < $ 1.0 (green) are compared. All distributions are normalized to the unity. The similar $ n_{\text{track}} $ distributions demonstrate that $ n_{\text{track}} $ and $ S_{\text{ML}} $ are decorrelated.

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Figure 5:
The distribution of $ d_{\text{BV}} $ in $ \mathrm{K^0_S} $ vertices between data (black) and simulation (purple) in Run-2. The lower panel shows the ratio between data and simulation. The data and simulation agree within 2% in all $ d_{\text{BV}} $ bins.

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Figure 6:
The vertex reconstruction efficiency (left) and ML tagging efficiency (right) in Run-2 data with artificially displaced vertices (black) and simulation (red). In this example, the artificially displaced vertices are corrected to mimic signal events with gluino mass of 2000 GeV and neutralino mass of 1800 GeV.

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Figure 6-a:
The vertex reconstruction efficiency (left) and ML tagging efficiency (right) in Run-2 data with artificially displaced vertices (black) and simulation (red). In this example, the artificially displaced vertices are corrected to mimic signal events with gluino mass of 2000 GeV and neutralino mass of 1800 GeV.

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Figure 6-b:
The vertex reconstruction efficiency (left) and ML tagging efficiency (right) in Run-2 data with artificially displaced vertices (black) and simulation (red). In this example, the artificially displaced vertices are corrected to mimic signal events with gluino mass of 2000 GeV and neutralino mass of 1800 GeV.

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Figure 7:
A schematic diagram of the signal (red), validation (yellow), and control (gray) regions.

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Figure 8:
The 95% CL upper limits on the product of cross section and the branching fraction squared in the full Run-2 dataset, shown as a function of gluino mass for a fixed $ c\tau $ of 0.1 mm, 10 mm, and 100 mm from top to bottom (respectively) with a mass splitting of 100 GeV (left) and 200 GeV (right). The gluino pair production cross sections with their uncertainty are shown as the red curves and bands.

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Figure 8-a:
The 95% CL upper limits on the product of cross section and the branching fraction squared in the full Run-2 dataset, shown as a function of gluino mass for a fixed $ c\tau $ of 0.1 mm, 10 mm, and 100 mm from top to bottom (respectively) with a mass splitting of 100 GeV (left) and 200 GeV (right). The gluino pair production cross sections with their uncertainty are shown as the red curves and bands.

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Figure 8-b:
The 95% CL upper limits on the product of cross section and the branching fraction squared in the full Run-2 dataset, shown as a function of gluino mass for a fixed $ c\tau $ of 0.1 mm, 10 mm, and 100 mm from top to bottom (respectively) with a mass splitting of 100 GeV (left) and 200 GeV (right). The gluino pair production cross sections with their uncertainty are shown as the red curves and bands.

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Figure 8-c:
The 95% CL upper limits on the product of cross section and the branching fraction squared in the full Run-2 dataset, shown as a function of gluino mass for a fixed $ c\tau $ of 0.1 mm, 10 mm, and 100 mm from top to bottom (respectively) with a mass splitting of 100 GeV (left) and 200 GeV (right). The gluino pair production cross sections with their uncertainty are shown as the red curves and bands.

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Figure 8-d:
The 95% CL upper limits on the product of cross section and the branching fraction squared in the full Run-2 dataset, shown as a function of gluino mass for a fixed $ c\tau $ of 0.1 mm, 10 mm, and 100 mm from top to bottom (respectively) with a mass splitting of 100 GeV (left) and 200 GeV (right). The gluino pair production cross sections with their uncertainty are shown as the red curves and bands.

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Figure 8-e:
The 95% CL upper limits on the product of cross section and the branching fraction squared in the full Run-2 dataset, shown as a function of gluino mass for a fixed $ c\tau $ of 0.1 mm, 10 mm, and 100 mm from top to bottom (respectively) with a mass splitting of 100 GeV (left) and 200 GeV (right). The gluino pair production cross sections with their uncertainty are shown as the red curves and bands.

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Figure 8-f:
The 95% CL upper limits on the product of cross section and the branching fraction squared in the full Run-2 dataset, shown as a function of gluino mass for a fixed $ c\tau $ of 0.1 mm, 10 mm, and 100 mm from top to bottom (respectively) with a mass splitting of 100 GeV (left) and 200 GeV (right). The gluino pair production cross sections with their uncertainty are shown as the red curves and bands.

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Figure 9:
The 95% CL upper limits on the product of cross section and the branching fraction squared in the full Run-2 dataset, shown as a function of $ c\tau $ for a fixed gluino mass of 1400 GeV (top) and 2000 GeV (bottom) with a mass splitting of 100 GeV (left) and 200 GeV (right). The gluino pair production cross sections with their uncertainty are shown as the red curves and bands.

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Figure 9-a:
The 95% CL upper limits on the product of cross section and the branching fraction squared in the full Run-2 dataset, shown as a function of $ c\tau $ for a fixed gluino mass of 1400 GeV (top) and 2000 GeV (bottom) with a mass splitting of 100 GeV (left) and 200 GeV (right). The gluino pair production cross sections with their uncertainty are shown as the red curves and bands.

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Figure 9-b:
The 95% CL upper limits on the product of cross section and the branching fraction squared in the full Run-2 dataset, shown as a function of $ c\tau $ for a fixed gluino mass of 1400 GeV (top) and 2000 GeV (bottom) with a mass splitting of 100 GeV (left) and 200 GeV (right). The gluino pair production cross sections with their uncertainty are shown as the red curves and bands.

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Figure 9-c:
The 95% CL upper limits on the product of cross section and the branching fraction squared in the full Run-2 dataset, shown as a function of $ c\tau $ for a fixed gluino mass of 1400 GeV (top) and 2000 GeV (bottom) with a mass splitting of 100 GeV (left) and 200 GeV (right). The gluino pair production cross sections with their uncertainty are shown as the red curves and bands.

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Figure 9-d:
The 95% CL upper limits on the product of cross section and the branching fraction squared in the full Run-2 dataset, shown as a function of $ c\tau $ for a fixed gluino mass of 1400 GeV (top) and 2000 GeV (bottom) with a mass splitting of 100 GeV (left) and 200 GeV (right). The gluino pair production cross sections with their uncertainty are shown as the red curves and bands.

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Figure 10:
The 95% CL upper limits on cross section times branching fraction squared in Run-2 for the split SUSY model with a mass splitting of 100 GeV (left) and 200 GeV (right), shown as a function of gluino mass and $ c\tau $. The observed (black) and expected (red) exclusion curves are overlaid on the limit plot. The gluino pair production cross sections with their uncertainty are shown as the red curves and bands.

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Figure 10-a:
The 95% CL upper limits on cross section times branching fraction squared in Run-2 for the split SUSY model with a mass splitting of 100 GeV (left) and 200 GeV (right), shown as a function of gluino mass and $ c\tau $. The observed (black) and expected (red) exclusion curves are overlaid on the limit plot. The gluino pair production cross sections with their uncertainty are shown as the red curves and bands.

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Figure 10-b:
The 95% CL upper limits on cross section times branching fraction squared in Run-2 for the split SUSY model with a mass splitting of 100 GeV (left) and 200 GeV (right), shown as a function of gluino mass and $ c\tau $. The observed (black) and expected (red) exclusion curves are overlaid on the limit plot. The gluino pair production cross sections with their uncertainty are shown as the red curves and bands.
Tables

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Table 1:
Summary of systematic uncertainties that affect the signal yield. The magnitude of each systematic varies by data-taking period and signal parameters, so the minimum and maximum values for each systematic uncertainty are reported.

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Table 2:
Number of predicted and observed events in the control, validation, and search regions. Regions are organized by $ S_{\text{ML}} $ and $ n_{\text{track}} $ values, and region names corresponding with Fig. 7 are given in parentheses. Specifically, the different columns correspond to events with $ n_{\text{track}} $ of 3, 4, and $ \geq $ 5. Predicted and observed number of events that pass or fail the $ S_{\text{ML}} $ selection are shown in different rows.
Summary
A search for the production of long-lived particles that decay to at least one displaced vertex with missing transverse momentum in proton-proton collisions at a center-of-mass energy of 13 TeV collected by the CMS detector is presented. The analysis extends the previous CMS search [24] by improving the sensitivity to events with low total jet energy, targeting events with as few as one displaced vertex, and introducing a dedicated machine learning algorithm. A benchmark signal model, split supersymmetry, is used for statistical interpretation in this search. The search sets 95% confidence level upper limits on long-lived gluinos with mass below 1800 GeV for mean proper decay lengths in the range of 1 to 100 mm, when the mass splitting is 100 GeV. For a 200 GeV mass splitting, gluinos with mass below 2000 GeV for mean proper decay lengths between 1 and 100 mm are excluded.
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