Quantum autoencoders for communication-efficient cloud computing
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42484_2023_112_ReferencePDF.pdf
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Author(s) • • • •
Zhu, Yan
Bai, Ge
Wang, Yuexuan
Li, Tongyang
Chiribella, Giulio
Date Issued
July 10, 2023
Publisher
Springer International Publishing
Citation
Quantum Machine Intelligence. 2023 Jul 10;5(2):27
Version
Author's final manuscript
Abstract
Abstract
In the model of quantum cloud computing, the server executes a computation on the quantum data provided by the client. In this scenario, it is important to reduce the amount of quantum communication between the client and the server. A possible approach is to transform the desired computation into a compressed version that acts on a smaller number of qubits, thereby reducing the amount of data exchanged between the client and the server. Here we propose quantum autoencoders for quantum gates (QAEGate) as a method for compressing quantum computations. We illustrate it in concrete scenarios of single-round and multi-round communication and validate it through numerical experiments. A bonus of our method is it does not reveal any information about the server’s computation other than the information present in the output.
MIT Department
Massachusetts Institute of Technology. Center for Theoretical Physics
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Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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DOI of Published Version
https://doi.org/10.1007/s42484-023-00112-5