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A quantum autoencoder functions as a type of quantum artificial neural network designed to compress sequences of quantum states through a training process. In this work, we analyze the compression performance of quantum autoencoders and obtain an asymptotic upper bound on the encoder’s compression rate.
Conference Presentation
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Alexei Kaltchenko
"Asymptotic compression rate of quantum autoencoders", Proc. SPIE 13028, Quantum Information Science, Sensing, and Computation XVI, 1302809 (7 June 2024); https://doi.org/10.1117/12.3013415
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Alexei Kaltchenko, "Asymptotic compression rate of quantum autoencoders," Proc. SPIE 13028, Quantum Information Science, Sensing, and Computation XVI, 1302809 (7 June 2024); https://doi.org/10.1117/12.3013415