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dc.contributor.authorWang, Y
dc.contributor.authorDong, D
dc.contributor.authorPetersen, IR
dc.date.accessioned2021-02-19T03:12:53Z
dc.date.available2021-02-19T03:12:53Z
dc.date.issued2017
dc.identifier.isbn9781509028733
dc.identifier.doi10.1109/CDC.2017.8264478
dc.identifier.urihttp://hdl.handle.net/10072/402401
dc.description.abstractAn approximate quantum Hamiltonian identification algorithm is presented with the assumption that the system initial state and observation matrix can be set appropriately. We sample the system with a fixed period and using the sampled data we estimate the Hamiltonian based on a Taylor expansion of the matrix exponential function. We prove the estimation error is linear in the variance of the additive Gaussian noise. We also propose a heuristic formula to find the order of magnitude of the optimal sampling period. Two numerical examples are presented to validate the theoretical results.
dc.description.peerreviewedYes
dc.publisherIEEE
dc.relation.ispartofconferencename56th Annual Conference on Decision and Control (CDC 2017)
dc.relation.ispartofconferencetitle2017 IEEE 56th Annual Conference on Decision and Control, CDC 2017
dc.relation.ispartofdatefrom2017-12-12
dc.relation.ispartofdateto2017-12-15
dc.relation.ispartoflocationMelbourne, Australia
dc.relation.ispartofpagefrom5523
dc.relation.ispartofpageto5528
dc.subject.fieldofresearchTheory of computation
dc.subject.fieldofresearchcode4613
dc.titleAn approximate quantum Hamiltonian identification algorithm using a Taylor expansion of the matrix exponential function
dc.typeConference output
dc.type.descriptionE1 - Conferences
dcterms.bibliographicCitationWang, Y; Dong, D; Petersen, IR, An approximate quantum Hamiltonian identification algorithm using a Taylor expansion of the matrix exponential function, 2017 IEEE 56th Annual Conference on Decision and Control, CDC 2017, 2017, pp. 5523-5528
dc.date.updated2021-02-19T03:11:17Z
dc.description.versionAccepted Manuscript (AM)
gro.rights.copyright© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
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gro.griffith.authorWang, Yuanlong


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