A hybrid GNN with a six-qubit circuit and a jet-multiplicity loss is claimed to improve classification of fully hadronic ttttW events over BDT and XGBoost in Monte Carlo, but the reported significance is inconsistent with the stated expected yields.
Figure 2 illustrates this graph representation, where nodes are categorized into jet nodes (blue) and b-jet nodes (orange), with edges 6 FIG
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Search for $t\bar tt\bar tW$ Production at $\sqrt{s} = 13$ TeV Using a Modified Graph Neural Network at the LHC
A hybrid GNN with a six-qubit circuit and a jet-multiplicity loss is claimed to improve classification of fully hadronic ttttW events over BDT and XGBoost in Monte Carlo, but the reported significance is inconsistent with the stated expected yields.