2026/06/02 by Haroon Sagheer, M. Tayyab Javaid, Ijaz Ahmed +2
#hep-ph
In this work, we study the single production of a vector-like singlet top partner \( T \) at the 14 TeV HL-LHC in the channel \( pp → T j \) with \( T → t Z \), \( t → b W → b j j \), and \( Z → νν \). Signal and background samples are generated with MadGraph5_aMC@NLO v3.5.11, showered with Pythia 8, and passed through Delphes. The dominant backgrounds are \( t t \), \( t Z j \), \( ZZ j j \), and \( W Z j j \) (including charge conjugates). A hadronic pre-selection (\( Nj ≥ 3 \), \( Nb ≥ 1 \), \( N_ℓ = 0 \)) is imposed as trigger, followed by optimized kinematic cuts. We perform multivariate classification with Extreme Gradient Boosting (XGBoost) and a Graph Neural Network (GNN) based on jet-level features. Sensitivities at 3000 fb\(-1\) are quoted using the Asimov significance, \( S / √(S + B) \), and an Asimov variant with a 20% background systematic. The model parameters \( g^* \) and \( RL \) are defined in Sec.~2, and a single global working point is used to avoid per-mass tuning bias. In the \( (g^*, mT) \) scan, we present 2\(σ\) exclusion and 5\(σ\) discovery contours for \( RL = 0 \) and \( RL = 0.5 \). For \( RL = 0 \), 2\(σ\) exclusion corresponds to \( g^* ∈ [0.17, 0.49] \) (\( 0.16, 0.43 \)) over \( mT ∈ [1.8, 2.7] \) TeV, while 5\(σ\) discovery corresponds to \( g^* ∈ [0.27, 0.44] \) (\( 0.26, 0.40 \)) over \( mT ∈ [1.8, 2.2] \) TeV for XGBoost and GNN respectively. For \( RL = 0.5 \), the 2\(σ\) reach is \( g^* ∈ [0.21, 0.48] \) (\( 0.20, 0.43 \)) over \( mT ∈ [1.8, 2.5] \) TeV, and the 5\(σ\) reach is \( g^* ∈ [0.33, 0.43] \) (\( 0.31, 0.49 \)) over \( mT ∈ [1.8, 2.2] \) TeV, with the GNN yielding slightly stronger and smoother limits across the scan.