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DOE OSTI · 1435294

Quantum Machine Learning over Infinite Dimensions

Lau, Hoi-Kwan·Pooser, Raphael·Siopsis, George·Weedbrook, Christian
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Abstract

Machine learning is a fascinating and exciting eld within computer science. Recently, this ex- citement has been transferred to the quantum information realm. Currently, all proposals for the quantum version of machine learning utilize the nite-dimensional substrate of discrete variables. Here we generalize quantum machine learning to the more complex, but still remarkably practi- cal, in nite-dimensional systems. We present the critical subroutines of quantum machine learning algorithms for an all-photonic continuous-variable quantum computer that achieve an exponential speedup compared to their equivalent classical counterparts. Finally, we also map out an experi- mental implementation which can be used as a blueprint for future photonic demonstrations.

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71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS

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Lau, Hoi-Kwan, Pooser, Raphael, Siopsis, George, Weedbrook, Christian. 2017-02-21. Quantum Machine Learning over Infinite Dimensions. https://doi.org/10.1103/physrevlett.118.080501

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