Speaker
Description
We propose a comprehensive search strategy for gluinos in the framework of General Gauge Mediation (GGM) at the high-luminosity LHC. Conventional GMSB searches at the LHC rely on a final state with multiple hard photons originating from the decay of a bino-higgsino-mixed NLSP into a gravitino LSP. As we have shown in our previous work, this strategy loses sensitivity over a significant portion of the GGM parameter space, where the cascade chain that ends at the photon-emitting NLSP is broken either by the direct decay of the gluino into a gluon and a gravitino, or by the gravitino decays of the heavier electroweakinos $\tilde\chi_{2,3}^0$ and $\tilde\chi_1^\pm$ into $W^\pm$, $Z$, or $h$ bosons accompanied by a gravitino. To restore sensitivity in these photon-deficient regions, we capture the boosted hadronic decays of the resulting electroweak bosons and top quarks using fat jets, identified by a graph-neural-network-based multi-class classifier built on the LorentzNet architecture. We organise the analysis into nine mutually exclusive signal regions characterised by photon, fat-jet, and lepton multiplicities, and use per-region boosted decision trees as the final discriminants in a binned profile-likelihood limit calculation. At $\sqrt{s} = 14$ TeV with $500~\text{fb}^{-1}$ of integrated luminosity, the combined analysis projects a $95\%$ CL expected exclusion on the gluino mass of up to $\sim 2.83$ TeV, with complementarity among the photonic, boosted-object, and dijet-plus-$E_T^{\rm miss}$ signal regions ensuring coverage across the full $(M_1, M_3)$ plane.