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Stealth Supersymmetry

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arxiv 1105.5135 v1 pith:T3EGS4SM submitted 2011-05-25 hep-ph

Stealth Supersymmetry

classification hep-ph
keywords breakingenergysmallsusymissingmodelsonlyr-parity
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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We present a broad class of supersymmetric models that preserve R-parity but lack missing energy signatures. These models have new light particles with weak-scale supersymmetric masses that feel SUSY breaking only through couplings to the MSSM. This small SUSY breaking leads to nearly degenerate fermion/boson pairs, with small mass splittings and hence small phase space for decays carrying away invisible energy. The simplest scenario has low-scale SUSY breaking, with missing energy only from soft gravitinos. This scenario is natural, lacks artificial tunings to produce a squeezed spectrum, and is consistent with gauge coupling unification. The resulting collider signals will be jet-rich events containing false resonances that could resemble signatures of R-parity violation. We discuss several concrete examples of the general idea, and emphasize gamma + jet + jet resonances, displaced vertices, and very large numbers of b-jets as three possible discovery modes.

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Cited by 3 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Search for massive, long-lived particles in events with displaced vertices and displaced muons in $pp$ collisions at $\sqrt{s}=13.6$ TeV with the ATLAS experiment

    hep-ex 2026-03 conditional novelty 6.0

    No signal of displaced-vertex-plus-displaced-muon events is seen in 164 fb^-1 of 13.6 TeV pp data; ATLAS sets improved 95% CL limits on RPV SUSY higgsino and stop production.

  2. Search for long-lived particles using displaced vertices with low-momentum tracks in proton-proton collisions at $\sqrt{s}$ = 13 TeV

    hep-ex 2025-11 conditional novelty 6.0

    A displaced-vertex search for compressed-spectrum long-lived particles excludes top squarks up to about 1100 GeV and wino-like neutralinos up to about 550 GeV, the strongest limits on these benchmark models.

  3. Shedding Light on Dark Matter at the LHC with Machine Learning

    hep-ph 2025-09 conditional novelty 5.0

    A machine-learned LHC analysis projects 5-sigma sensitivity to singlino-dominated NMSSM dark matter via radiative higgsino decays to photons, covering higgsino masses up to 225 GeV.