Quantum gate identification: Error analysis, numerical results and optical experiment
dc.contributor.author | Wang, Yuanlong | |
dc.contributor.author | Yin, Qi | |
dc.contributor.author | Dong, Daoyi | |
dc.contributor.author | Qi, Bo | |
dc.contributor.author | Petersen, Ian | |
dc.contributor.author | Hou, Zhibo | |
dc.contributor.author | Yonezawa, Hidehiro | |
dc.contributor.author | Xiang, Guoyong | |
dc.date.accessioned | 2020-04-01T01:41:48Z | |
dc.date.issued | 2019-03 | |
dc.date.updated | 2019-11-25T07:46:28Z | |
dc.description.abstract | The identification of an unknown quantum gate is a significant issue in quantum technology. In this paper, we propose a quantum gate identification method within the framework of quantum process tomography. In this method, a series of pure states are applied to the gate and then a fast state tomography on the output states is performed and the data are used to reconstruct the quantum gate. The algorithm has computational complexity with the system dimension . The identification approach is compared with the maximum likelihood estimation method for the running time, which shows an efficiency advantage of our method. An error upper bound is established for the identification algorithm and the robustness of the algorithm against impurities in the input states is also tested. We perform a quantum optical experiment on a single-qubit Hadamard gate to verify the effectiveness of the identification algorithm. | en_AU |
dc.description.sponsorship | This work was supported by the Australian Research Council’s Discovery Projects funding scheme under Project DP190101566, Laureate Fellowship FL110100020, AFOSR under grant FA2386-16-1-4065, Centres of Excellence CE110001027, the National Natural Science Foundation of China (Nos. 61773370, 61828303, 61833010, 11574291, 11774334, 11688101). | en_AU |
dc.format.extent | 11 pages | en_AU |
dc.format.mimetype | application/pdf | en_AU |
dc.identifier.issn | 0005-1098 | en_AU |
dc.identifier.uri | http://hdl.handle.net/1885/202601 | |
dc.language.iso | en_AU | en_AU |
dc.publisher | Pergamon-Elsevier Ltd | en_AU |
dc.relation | http://purl.org/au-research/grants/arc/DP190101566 | en_AU |
dc.relation | http://purl.org/au-research/grants/arc/FL110100020 | en_AU |
dc.relation | http://purl.org/au-research/grants/arc/CE110001027 | en_AU |
dc.rights | © 2018 Elsevier Ltd. | en_AU |
dc.source | Automatica | en_AU |
dc.subject | Quantum system, Quantum tomography, Quantum gate identification, Computational complexity | en_AU |
dc.title | Quantum gate identification: Error analysis, numerical results and optical experiment | en_AU |
dc.type | Journal article | en_AU |
dcterms.dateAccepted | 2018-11-26 | |
local.bibliographicCitation.lastpage | 279 | en_AU |
local.bibliographicCitation.startpage | 269 | en_AU |
local.contributor.affiliation | Wang, Yuanlong, University of New South Wales | en_AU |
local.contributor.affiliation | Yin, Qi, University of Science and Technology of China | en_AU |
local.contributor.affiliation | Dong, Daoyi, University of New South Wales | en_AU |
local.contributor.affiliation | Qi, Bo, Chinese Academy of Sciences | en_AU |
local.contributor.affiliation | Petersen, Ian, College of Engineering and Computer Science, The Australian National University | en_AU |
local.contributor.affiliation | Hou, Zhibo, University of Science and Technology of China | en_AU |
local.contributor.affiliation | Yonezawa, Hidehiro, The University of New South Wales | en_AU |
local.contributor.affiliation | Xiang, Guoyong, University of Science and Technology of China | en_AU |
local.contributor.authoruid | Petersen, Ian, u4036493 | en_AU |
local.description.embargo | 2037-12-31 | |
local.description.notes | Imported from ARIES. AAM requested but author unable to supply (JS 1/4/2020) | en_AU |
local.identifier.absfor | 090602 - Control Systems, Robotics and Automation | en_AU |
local.identifier.absseo | 970109 - Expanding Knowledge in Engineering | en_AU |
local.identifier.ariespublication | u3102795xPUB911 | en_AU |
local.identifier.citationvolume | 101 | en_AU |
local.identifier.doi | 10.1016/j.automatica.2018.12.011 | en_AU |
local.identifier.scopusID | 2-s2.0-85059329959 | |
local.publisher.url | https://www.elsevier.com/ | en_AU |
local.type.status | Published Version | en_AU |
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