A variational quantum classifier trained on one-turn particle trajectories predicts dynamic aperture boundaries of the WHPS low-energy ring with accuracy close to, and at small sample sizes slightly better than, a small classical neural network.
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Application of quantum machine learning using variational quantum classifier in accelerator physics
A variational quantum classifier trained on one-turn particle trajectories predicts dynamic aperture boundaries of the WHPS low-energy ring with accuracy close to, and at small sample sizes slightly better than, a small classical neural network.