Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/239047
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dc.titleOVERLAP MEASUREMENT OF INFINITE DIMENSIONAL QUANTUM STATES AND BOSONIC LEARNING MACHINE WITH TRAPPED IONS
dc.contributor.authorTSENG KO-WEI
dc.date.accessioned2023-04-30T18:00:33Z
dc.date.available2023-04-30T18:00:33Z
dc.date.issued2023-01-13
dc.identifier.citationTSENG KO-WEI (2023-01-13). OVERLAP MEASUREMENT OF INFINITE DIMENSIONAL QUANTUM STATES AND BOSONIC LEARNING MACHINE WITH TRAPPED IONS. ScholarBank@NUS Repository.
dc.identifier.urihttps://scholarbank.nus.edu.sg/handle/10635/239047
dc.description.abstractWe describe the implementation of the controlled beam splitter (CBS) gate to create entanglement between the spins and motional modes of trapped 171Yb+ ions. We combine two CBS gates to demonstrate the SWAP test between two infinitely dimensional states encoded in the motional modes. To characterise the SWAP test , we measure the overlap between the Fock states, superposition of Fock states, coherent states, squeezed vacuum states and cat states, with a constant-depth circuit. With the SWAP test and ability to prepare arbitrary state of a harmonic oscillator based on the Eberly-Law method, we successfully implement two quantum machine learning algorithms: the supervised k-NN and unsupervised K-means cluster algorithm. We first correctly group the 15 unlabeled quantum states into three clusters in three iterations of the K-means cluster algorithm. Next, the k-NN algorithm uses the previously described 15 quantum states as the training states to identify patterns in five trial states.
dc.language.isoen
dc.subjecttrapped ions; quantum computing; continuous variables; swap test; overlap measurement; quantum machine learning
dc.typeThesis
dc.contributor.departmentCENTRE FOR QUANTUM TECHNOLOGIES
dc.contributor.supervisorDzmitry Matsukevich
dc.description.degreePh.D
dc.description.degreeconferredDOCTOR OF PHILOSOPHY (CQT)
dc.identifier.orcid0000-0003-1244-228X
Appears in Collections:Ph.D Theses (Open)

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