Quantum state discrimination using noisy quantum neural networks

@article{Patterson2021QuantumSD,
  title={Quantum state discrimination using noisy quantum neural networks},
  author={Andrew D. Patterson and Hongxiang Chen and Leonard Wossnig and Simone Severini and Dan E. Browne and Ivan Rungger},
  journal={Physical Review Research},
  year={2021}
}
Near-term quantum computers are noisy, and therefore must run algorithms with a low circuit depth and qubit count. Here we investigate how noise affects a quantum neural network (QNN) for state discrimination, applicable on near-term quantum devices as it fulfils the above criteria. We find that when simulating gradient calculation on a noisy device, a large number of parameters is disadvantageous. By introducing a new smaller circuit ansatz we overcome this limitation, and find that the QNN… 
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