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We investigate the potential for detecting higgsinos at the LHC, where their small production cross-sections pose significant challenges. Focusing on a simplified supersymmetric model with R-parity violation via a baryon-number-violating trilinear coupling, we analyze higgsino masses in the 400–1000 GeV range. Utilizing a machine learning-based top tagger to identify boosted top jets from higgsino decays, we employ a BDT classifier to enhance signal discrimination against Standard Model backgrounds. Our analysis defines two signal regions based on top jets and varying b-jet and light jet multiplicities. Combining results from both regions, we demonstrate that higgsino masses up to 925 GeV can be probed at the high-luminosity LHC.

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Probing Sub-teV Higgsinos in a Trilinear RPV SUSY Scenario Using GNN-Based Boosted Top Tagger

  • 会议论文

  • 发表日期：

    2025年

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  • Rajneil Baruah,
  • Arghya Choudhury,
  • Kirtiman Ghosh,
  • Subhadeep Mondal,
  • Rameswar Sahu

摘要

We investigate the potential for detecting higgsinos at the LHC, where their small production cross-sections pose significant challenges. Focusing on a simplified supersymmetric model with R-parity violation via a baryon-number-violating trilinear coupling, we analyze higgsino masses in the 400–1000 GeV range. Utilizing a machine learning-based top tagger to identify boosted top jets from higgsino decays, we employ a BDT classifier to enhance signal discrimination against Standard Model backgrounds. Our analysis defines two signal regions based on top jets and varying b-jet and light jet multiplicities. Combining results from both regions, we demonstrate that higgsino masses up to 925 GeV can be probed at the high-luminosity LHC.