Supervised learning of random quantum circuits via scalable neural networks

@article{Cantori2022SupervisedLO,
  title={Supervised learning of random quantum circuits via scalable neural networks},
  author={S. Cantori and Diego Vitali and S. Pilati},
  journal={ArXiv},
  year={2022},
  volume={abs/2206.10348}
}
Predicting the output of quantum circuits is a hard computational task that plays a pivotal role in the development of universal quantum computers. Here we investigate the supervised learning of output expectation values of random quantum circuits. Deep convolutional neural networks (CNNs) are trained to predict single-qubit and two-qubit expectation values using databases of classically simulated circuits. These circuits are represented via an appropriately designed one-hot encoding of the… 

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