Related papers: Tensor networks for quantum machine learning

Tensor networks for quantum machine learning

URL: http://arxiv.org/abs/2303.11735v1
Date: Tue, 21 Mar 2023 10:46:56 GMT
Title: Tensor networks for quantum machine learning
Authors: Hans-Martin Rieser, Frank K\"oster and Arne Peter Raulf
Abstract summary: We discuss how layouts like MPS, PEPS, TTNs and MERA can be mapped to a quantum computer. We also discuss how they can be used for machine learning and data encoding and which implementation techniques improve their performance.
Score: 0.0
License: http://creativecommons.org/licenses/by/4.0/
Abstract: Once developed for quantum theory, tensor networks have been established as a successful machine learning paradigm. Now, they have been ported back to the quantum realm in the emerging field of quantum machine learning to assess problems that classical computers are unable to solve efficiently. Their nature at the interface between physics and machine learning makes tensor networks easily deployable on quantum computers. In this review article, we shed light on one of the major architectures considered to be predestined for variational quantum machine learning. In particular, we discuss how layouts like MPS, PEPS, TTNs and MERA can be mapped to a quantum computer, how they can be used for machine learning and data encoding and which implementation techniques improve their performance.

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