Search for top squarks in final states with many
light-flavor jets and 0, 1, or 2 charged leptons in
proton-proton collisions at √s = 13 TeV
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13130_2025_Article_27529.pdf
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Author(s)
Chekhovsky, V.
Hayrapetyan, A.
Makarenko, V.
Tumasyan, A.
Adam, W.
Andrejkovic, J. W.
Benato, L.
Bergauer, T.
Chatterjee, S.
Damanakis, K.
Date Issued
October 29, 2025
Journal
Journal of High Energy Physics
Publisher
Springer Berlin Heidelberg
Citation
The CMS collaboration., Chekhovsky, V., Hayrapetyan, A. et al. Search for top squarks in final states with many light-flavor jets and 0, 1, or 2 charged leptons in proton-proton collisions at √s = 13 TeV. J. High Energ. Phys. 2025, 236 (2025).
Version
Final published version
Abstract
Several new physics models including versions of supersymmetry (SUSY) characterized by R-parity violation (RPV) or with additional hidden sectors predict the production of events with top quarks, low missing transverse momentum, and many additional quarks or gluons. The results of a search for top squarks decaying to two top quarks and six additional light-flavor quarks or gluons are reported. The search employs a novel machine learning method for background estimation from control samples in data using decorrelated discriminators. The search is performed using events with 0, 1, or 2 electrons or muons in conjunction with at least six jets. No requirement is placed on the magnitude of the missing transverse momentum. The result is based on a sample of proton-proton collisions at $$\sqrt{s}=13$$ TeV corresponding to 138 fb−1 of integrated luminosity collected with the CMS detector at the LHC in 2016–2018. With no statistically significant excess of events observed beyond the expected contributions from the standard model, the data are used to determine upper limits on the top squark pair production cross section in the frameworks of RPV and stealth SUSY. Models with top squark masses less than 700 (930) GeV are excluded at 95% confidence level for RPV (stealth) SUSY scenarios.
MIT Department
Massachusetts Institute of Technology. Laboratory for Nuclear Science
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
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DOI of Published Version
https://doi.org/10.1007/JHEP10(2025)236
