DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kim, Changjun | ko |
dc.contributor.author | Rhee, June-Koo Kevin | ko |
dc.contributor.author | Lee, Woojun | ko |
dc.contributor.author | Ahn, Jaewook | ko |
dc.date.accessioned | 2023-07-04T02:02:31Z | - |
dc.date.available | 2023-07-04T02:02:31Z | - |
dc.date.created | 2023-06-08 | - |
dc.date.created | 2023-06-08 | - |
dc.date.issued | 2018-10 | - |
dc.identifier.citation | 9th International Conference on Information and Communication Technology Convergence, ICTC 2018, pp.740 - 747 | - |
dc.identifier.uri | http://hdl.handle.net/10203/310244 | - |
dc.description.abstract | In traditional quantum measurements, the size of tomography increases exponentially with the growth of qubit counts. In this paper, we introduce machine learning techniques such as Deep Neural Network (DNN) and Long Short Term Memory (LSTM) to analyze the Quantum Density Matrix up to 4 qubits, with no assumption of governing model. | - |
dc.language | English | - |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | - |
dc.title | Mixed Quantum State Dynamics Estimation with Artificial Neural Network | - |
dc.type | Conference | - |
dc.identifier.wosid | 000517984800157 | - |
dc.identifier.scopusid | 2-s2.0-85059461674 | - |
dc.type.rims | CONF | - |
dc.citation.beginningpage | 740 | - |
dc.citation.endingpage | 747 | - |
dc.citation.publicationname | 9th International Conference on Information and Communication Technology Convergence, ICTC 2018 | - |
dc.identifier.conferencecountry | KO | - |
dc.identifier.conferencelocation | Jeju Island | - |
dc.identifier.doi | 10.1109/ICTC.2018.8539575 | - |
dc.contributor.localauthor | Rhee, June-Koo Kevin | - |
dc.contributor.localauthor | Ahn, Jaewook | - |
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