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Control of five-qubit system based on quantum reinforcement learning

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dc.contributor.authorDong, Daoyien
dc.contributor.authorChen, Zonghaien
dc.contributor.authorChen, Chunlinen
dc.contributor.authorZhang, Chenbinen
dc.date.accessioned2025-03-23T06:25:34Z
dc.date.available2025-03-23T06:25:34Z
dc.date.issued2006en
dc.description.abstractControlling the multi-qubit system is a key task for practical quantum information processing. In this paper, the control problem of five-qubit is studied. A novel quantum reinforcement learning algorithm based on quantum superposition principle is proposed for the quantum control problem. The simulated result shows that quantum reinforcement learning can effectively find the optimal control sequence through fast learning.en
dc.description.statustrueen
dc.format.extent4en
dc.identifier.isbn1424406056en
dc.identifier.isbn9781424406050en
dc.identifier.otherScopus:38549140524en
dc.identifier.urihttps://dspace-test.anu.edu.au/handle/1885/733731300
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=38549140524&partnerID=8YFLogxKen
dc.language.isoEnglishen
dc.relation.ispartofseries2006 International Conference on Computational Intelligence and Security, ICCIAS 2006en
dc.titleControl of five-qubit system based on quantum reinforcement learningen
dc.typeConference contributionen
local.bibliographicCitation.lastpage167en
local.bibliographicCitation.startpage164en
local.contributor.affiliationDong, Daoyi; University of Science and Technology of Chinaen
local.contributor.affiliationChen, Zonghai; University of Science and Technology of Chinaen
local.contributor.affiliationChen, Chunlin; Nanjing Universityen
local.contributor.affiliationZhang, Chenbin; University of Science and Technology of Chinaen
local.identifier.doi10.1109/ICCIAS.2006.294113en
local.identifier.pure277a7df9-b235-4995-b4a8-4d11bc080cd9en
local.type.statusPublisheden

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