A quantum autoencoder: Using machine learning to compress qutrits
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Tischler, N
Pryde, GJ
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Sydney Australia
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Abstract
The compression of quantum data will allow increased control over difficult-to- manage quantum resources. We experimentally realize a quantum autoencoder, which learns to compress quantum data with a classical machine learning routine.
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14th Pacific Rim Conference on Lasers and Electro-Optics (CLEO PR 2020) - Proceedings
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© 2020 Optical Society of America. The attached file is reproduced here in accordance with the copyright policy of the publisher. Please refer to the conference's website for access to the definitive, published version.
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Atomic, molecular and optical physics
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Pepper, A; Tischler, N; Pryde, GJ, A quantum autoencoder: Using machine learning to compress qutrits, 14th Pacific Rim Conference on Lasers and Electro-Optics (CLEO PR 2020) - Proceedings, 2020