File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Article: Quantum autoencoders for communication-efficient cloud computing

TitleQuantum autoencoders for communication-efficient cloud computing
Authors
KeywordsQuantum autoencoders
Quantum cloud computing
Quantum gate
Issue Date10-Jul-2023
PublisherSpringer
Citation
Quantum Machine Intelligence, 2023, v. 5, n. 2 How to Cite?
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.


Persistent Identifierhttp://hdl.handle.net/10722/331297
ISSN

 

DC FieldValueLanguage
dc.contributor.authorZhu, Y-
dc.contributor.authorBai, G-
dc.contributor.authorWang, YX-
dc.contributor.authorLi, TY-
dc.contributor.authorChiribella, G-
dc.date.accessioned2023-09-21T06:54:28Z-
dc.date.available2023-09-21T06:54:28Z-
dc.date.issued2023-07-10-
dc.identifier.citationQuantum Machine Intelligence, 2023, v. 5, n. 2-
dc.identifier.issn2524-4906-
dc.identifier.urihttp://hdl.handle.net/10722/331297-
dc.description.abstract<p></p><p>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.<br></p>-
dc.languageeng-
dc.publisherSpringer-
dc.relation.ispartofQuantum Machine Intelligence-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectQuantum autoencoders-
dc.subjectQuantum cloud computing-
dc.subjectQuantum gate-
dc.titleQuantum autoencoders for communication-efficient cloud computing-
dc.typeArticle-
dc.identifier.doi10.1007/s42484-023-00112-5-
dc.identifier.scopuseid_2-s2.0-85164279491-
dc.identifier.volume5-
dc.identifier.issue2-
dc.identifier.eissn2524-4914-
dc.identifier.issnl2524-4906-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats