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| CMS-EXO-22-020 ; CERN-EP-2024-031 | ||
| Search for long-lived particles using displaced vertices and missing transverse momentum in proton-proton collisions at $ \sqrt{s}= $ 13 TeV | ||
| CMS Collaboration | ||
| 24 February 2024 | ||
| Submitted to Phys. Rev. D | ||
| Abstract: A search for the production of long-lived particles 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, 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. A machine learning algorithm, which improves the background rejection power by more than an order of magnitude, is applied to improve the sensitivity. The observation is consistent with the standard model background prediction, and the results are used to constrain split supersymmetry (SUSY) and gauge-mediated SUSY breaking models with different gluino mean proper decay lengths and masses. This search is the first CMS search that shows sensitivity to hadronically decaying long-lived particles from signals with mass differences between the gluino and neutralino below 100 GeV. It sets the most stringent limits to date for split-SUSY models and gauge-mediated SUSY breaking models with gluino proper decay length less than 6 mm. | ||
| Links: e-print arXiv:2402.15804 [hep-ex] (PDF) ; CDS record ; inSPIRE record ; HepData record ; CADI line (restricted) ; | ||
| Figures | |
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Figure 1:
Diagrams of the split-SUSY model (left) and GMSB SUSY model (right). In the split-SUSY model, a pair of long-lived gluinos is produced, and each decays to two quarks and one neutralino. In the GMSB SUSY model, a pair of long-lived gluinos is produced, and each decays to a gluon and a gravitino. |
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Figure 1-a:
Diagrams of the split-SUSY model (left) and GMSB SUSY model (right). In the split-SUSY model, a pair of long-lived gluinos is produced, and each decays to two quarks and one neutralino. In the GMSB SUSY model, a pair of long-lived gluinos is produced, and each decays to a gluon and a gravitino. |
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Figure 1-b:
Diagrams of the split-SUSY model (left) and GMSB SUSY model (right). In the split-SUSY model, a pair of long-lived gluinos is produced, and each decays to two quarks and one neutralino. In the GMSB SUSY model, a pair of long-lived gluinos is produced, and each decays to a gluon and a gravitino. |
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Figure 2:
An illustration of 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 original input information ($ O $) is integrated with relation matrices ($ R_{\text{r}} $ and $ R_{\text{s}} $) to form a graph that captures interactions between tracks. This graph is subsequently processed by an MLP ($ \phi_{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 $. To assess the influence ($ P $) of the effect on the original information, it undergoes further processing via another MLP ($ \phi_{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 data, simulated background, and signal. Events with $ n_{\text{track}} $ of 3 (upper), 4 (middle), and $ \geq $5 (lower) 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 and mass difference between the gluino and neutralino, are shown as $ c\tau $ and $ \Delta m $ in the legend. All distributions are normalized to unity. |
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Figure 3-a:
Distributions of $ S_{\text{ML}} $ for data, simulated background, and signal. Events with $ n_{\text{track}} $ of 3 (upper), 4 (middle), and $ \geq $5 (lower) 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 and mass difference between the gluino and neutralino, are shown as $ c\tau $ and $ \Delta m $ in the legend. All distributions are normalized to unity. |
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Figure 3-b:
Distributions of $ S_{\text{ML}} $ for data, simulated background, and signal. Events with $ n_{\text{track}} $ of 3 (upper), 4 (middle), and $ \geq $5 (lower) 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 and mass difference between the gluino and neutralino, are shown as $ c\tau $ and $ \Delta m $ in the legend. All distributions are normalized to unity. |
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Figure 3-c:
Distributions of $ S_{\text{ML}} $ for data, simulated background, and signal. Events with $ n_{\text{track}} $ of 3 (upper), 4 (middle), and $ \geq $5 (lower) 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 and mass difference between the gluino and neutralino, are shown as $ c\tau $ and $ \Delta m $ in the legend. All distributions are normalized to unity. |
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Figure 3-d:
Distributions of $ S_{\text{ML}} $ for data, simulated background, and signal. Events with $ n_{\text{track}} $ of 3 (upper), 4 (middle), and $ \geq $5 (lower) 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 and mass difference between the gluino and neutralino, are shown as $ c\tau $ and $ \Delta m $ in the legend. All distributions are normalized to unity. |
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Figure 3-e:
Distributions of $ S_{\text{ML}} $ for data, simulated background, and signal. Events with $ n_{\text{track}} $ of 3 (upper), 4 (middle), and $ \geq $5 (lower) 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 and mass difference between the gluino and neutralino, are shown as $ c\tau $ and $ \Delta m $ in the legend. All distributions are normalized to unity. |
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Figure 3-f:
Distributions of $ S_{\text{ML}} $ for data, simulated background, and signal. Events with $ n_{\text{track}} $ of 3 (upper), 4 (middle), and $ \geq $5 (lower) 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 and mass difference between the gluino and neutralino, are shown as $ c\tau $ and $ \Delta m $ in the legend. All distributions are normalized to unity. |
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Figure 4:
The distribution of $ n_{\text{track}} $ in different $ S_{\text{ML}} $ regions for simulated background events. 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 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_{\mathrm{BV}} $ in $ \mathrm{K^0_S} $ vertices in data (black) and simulation (purple). The lower panel shows the ratio between data and simulation. |
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Figure 6:
The vertex reconstruction efficiency (left) and ML tagging efficiency (right) for artificially displaced vertices in data (black) and simulation (red). In this example, the artificially displaced vertices are corrected to mimic split-SUSY signal events with gluino mass of 2000 GeV and neutralino mass of 1800 GeV. The uncertainties are too small to be visible in the plot. |
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Figure 6-a:
The vertex reconstruction efficiency (left) and ML tagging efficiency (right) for artificially displaced vertices in data (black) and simulation (red). In this example, the artificially displaced vertices are corrected to mimic split-SUSY signal events with gluino mass of 2000 GeV and neutralino mass of 1800 GeV. The uncertainties are too small to be visible in the plot. |
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Figure 6-b:
The vertex reconstruction efficiency (left) and ML tagging efficiency (right) for artificially displaced vertices in data (black) and simulation (red). In this example, the artificially displaced vertices are corrected to mimic split-SUSY signal events with gluino mass of 2000 GeV and neutralino mass of 1800 GeV. The uncertainties are too small to be visible in the plot. |
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Figure 7:
A schematic diagram of the signal (red), validation (yellow), and control (gray) regions. The letter in each box corresponds to the region label described in the text. |
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Figure 8:
Left: the 95% $ \text{CL}_\text{s} $ upper limit on the product of the cross section and branching fraction squared for the split-SUSY signal model with a mass splitting of 100 GeV, shown as a function of gluino mass and $ c\tau $. Right: the 95% $ \text{CL}_\text{s} $ upper limit on the product of the cross section and branching fraction squared for the split-SUSY model with a $ c\tau $ of 10 mm, shown as a function of gluino mass and mass splitting. For both plots, the observed (solid black) and expected (dashed red) exclusion curves are shown. |
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Figure 8-a:
Left: the 95% $ \text{CL}_\text{s} $ upper limit on the product of the cross section and branching fraction squared for the split-SUSY signal model with a mass splitting of 100 GeV, shown as a function of gluino mass and $ c\tau $. Right: the 95% $ \text{CL}_\text{s} $ upper limit on the product of the cross section and branching fraction squared for the split-SUSY model with a $ c\tau $ of 10 mm, shown as a function of gluino mass and mass splitting. For both plots, the observed (solid black) and expected (dashed red) exclusion curves are shown. |
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Figure 8-b:
Left: the 95% $ \text{CL}_\text{s} $ upper limit on the product of the cross section and branching fraction squared for the split-SUSY signal model with a mass splitting of 100 GeV, shown as a function of gluino mass and $ c\tau $. Right: the 95% $ \text{CL}_\text{s} $ upper limit on the product of the cross section and branching fraction squared for the split-SUSY model with a $ c\tau $ of 10 mm, shown as a function of gluino mass and mass splitting. For both plots, the observed (solid black) and expected (dashed red) exclusion curves are shown. |
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Figure 9:
The 95% $ \text{CL}_\text{s} $ upper limit on the product of the cross section and branching fraction squared for the GMSB SUSY signal model, shown as a function of gluino mass and $ c\tau $. The observed (solid black) and expected (dashed red) exclusion curves are shown. |
| 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 a range of values is given in each case. |
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Table 2:
Number of predicted and observed events in the control, validation, and search regions. Predictions are calculated using Eqs. (2) and (3) and fitting the data under the background-only hypothesis. Regions are organized by $ S_{\text{ML}} $ and $ n_{\text{track}} $ values, and region names corresponding to Fig. 7 are given in parentheses. The predicted number of events that pass the $ S_{\text{ML}} $ selection and the observed number of events that pass or fail the $ S_{\text{ML}} $ selection are shown in separate 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 has been 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 that reduces the number of background events in the signal region by 94%. Split supersymmetry (SUSY) and gauge-mediated SUSY breaking are used as benchmark signal models for statistical interpretations in this search. At 95% confidence level, the search excludes long-lived gluinos predicted by the split-SUSY model with masses below 1800 GeV and mean proper decay lengths in the range of 1 to 100 mm, when the mass splitting is 100 GeV. For mass splittings above 50 GeV, gluinos with masses below 1600 GeV and mean proper decay lengths between 1 and 30 mm are excluded. For the gauge-mediated SUSY breaking model, gluinos with masses below 2200 GeV and mean proper decay lengths between 0.3 and 100 mm are excluded. This search is the first CMS search that shows sensitivity to hadronically decaying long-lived particles from signals with mass differences between the gluino and neutralino below 100 GeV. It sets the most stringent limits to date for split-SUSY models and for GMSB gluinos with proper decay length less than 6 mm. |
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