Quantum Graph Neural Networks for Jet Tagging on Quantum Hardware
A preprint on arXiv reports a study applying quantum graph neural networks to jet classification, motivated by jet measurements at the Large Hadron Collider and the future Electron-Ion Collider. The authors explore quantum machine learning methods for jet tagging and present an implementation intended to run on quantum hardware.
This preprint could become a reference benchmark for quantum GNN jet tagging on small datasets, with follow-up papers testing variations in encoding and circuit depth across cloud-accessible quantum processors.