Quantum generalisation of feedforward neural networks

@article{Wan2016QuantumGO,
  title={Quantum generalisation of feedforward neural networks},
  author={Kwok Ho Wan and O. Dahlsten and Hl{\'e}r Kristj{\'a}nsson and Robert Gardner and M. Kim},
  journal={npj Quantum Information},
  year={2016},
  volume={3},
  pages={1-8}
}
We propose a quantum generalisation of a classical neural network. The classical neurons are firstly rendered reversible by adding ancillary bits. Then they are generalised to being quantum reversible, i.e., unitary (the classical networks we generalise are called feedforward, and have step-function activation functions). The quantum network can be trained efficiently using gradient descent on a cost function to perform quantum generalisations of classical tasks. We demonstrate numerically that… Expand
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