• Corpus ID: 253735411

A duplication-free quantum neural network for universal approximation

@inproceedings{Hou2022ADQ,
  title={A duplication-free quantum neural network for universal approximation},
  author={Xiaokai Hou and Guanyu Zhou and Qing Li and Shan Jin and Xiaoting Wang},
  year={2022}
}
The universality of a quantum neural network refers to its ability to approximate arbitrary functions and is a theoretical guarantee for its effectiveness. A non-universal neural network could fail in completing the machine learning task. One proposal for universality is to encode the quantum data into identical copies of a tensor product, but this will substantially increase the system size and the circuit complexity. To address this problem, we propose a simple design of a duplication-free… 
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