Towards quantum machine learning with tensor networks

William Huggins, Piyush Patil, Bradley Mitchell et al.

2018 · Quantum Science and Technology · 303 citations

Abstract Machine learning is a promising application of quantum computing, but challenges remain for implementation today because near-term devices have a limited number of physical qubits and high error rates. Motivated by the usefulness of tensor networks for machine learning in the classical context, we propose quantum computing approaches to both discriminative and generative learning, with circuits based on tree and matrix product state tensor networks, that could already have benefits with such near-term devices. The result is a unified framework in which classical and quantum computing…

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